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Data Science Personal Statement Sample and Examples

Home Blog Data Science Data Science Personal Statement Sample and Examples

Data science is one of the most popular career options for students, especially those pursuing a Bachelor's degree. It is also one of the most sought-after courses in universities today. If you just want some ideas on how to write a personal statement for data science, then this article is for you. Also, if you’re someone who is willing to secure a career in the field of data science, then it is recommended that you pursue Data Science Courses that will enable you to learn all aspe that will enable you to learn all aspects and principles of data science. 

What is a Data Science Personal Statement?

In a nutshell, the personal statement for data science is a document that you write to explain why you are interested in pursuing the subject and what you can bring to the table. It should be written in a way that shows your interest in the subject and why you want to study it. You may want to include information about the following in your data science personal statement.  

• What led up to your decision to pursue this field? 
• Why do data scientists matter? What problems need solving by them? What value do they provide society as well as individuals? 
• How will studying this specific field help prepare you for future careers or additional educational opportunities (e-learning programs, etc.)?

You can also include the following:  

• What are your goals for this degree?  
• How will it benefit you?  
• What do you hope to achieve from studying data science?  
• Why is this field important in today’s society?  
• What are the challenges that you see in this field?  
• How will you address those challenges?  
• What do you think the future of data science is?  
• How do you plan on staying relevant as technologies and trends change?

The Importance of Creating a Data Science Personal Statement

Data science personal statement is a formal document that will be used by the company to evaluate your skills. If you are applying for a Data Science job and want to impress the hiring manager, then you must write a strong data science personal statement.

A good personal statement for a master's in data science must be unique, creative, informative and interesting to read. It should describe not only your skills and experience but also showcase your ability to think critically and creatively.

A well-written data science personal statement will help you stand out from other applicants and make yourself an ideal candidate for the job that you want. Here are some useful tips for writing a strong data science personal statement: 

• Be honest and straightforward in your personal statement. 
• Don’t exaggerate or lie about your skills, experience and achievements. If you don’t have any relevant work experience, then focus on other areas where you can showcase your skills, such as volunteering or community projects. 
• Know the company that you are applying to and tailor your personal statement accordingly. A generic resume won’t help if you are applying for a specific job position. Instead, write a customized letter that shows how well-suited you are for this role. 
• Keep it short and sweet. The best personal statements are between a few hundred to a few thousand words long. Don’t try to cram everything in one big paragraph; break it up into smaller sections that will make it easier for readers to digest. 

So now you might have understood how important data analytics personal statements are. To learn how to create a personal statement, it is recommended that you enroll in the Best Data Science Bootcamps . 

Data Science Personal Statement Sample

I am writing this Data Science Personal Statement for the MS in Data Science program at UC Berkeley. My goal is to explain why I want to pursue a career in data science and how my experience as an undergraduate student has prepared me for graduate school. As you can see from my resume, I have had many opportunities to work with large amounts of data through internships and research projects over the course of my academic career. These experiences have given me valuable insight into how large-scale computational problems can be tackled by applying statistical methods under tight deadlines while still maintaining quality control over your results. 

In addition, I have taken classes such as AI/ML Systems Design & Implementation and Machine Learning Algorithms. These classes have helped me develop new ways of approaching problems while also providing an understanding of why certain algorithms work better than others when applied in specific situations. 

I am a Data Science Major at UC Berkeley and have been for two years. In order to graduate with a major in Data Science, you must complete four required classes, one of which is an independent study project. 

I have chosen to take this independent study project in order to gain hands-on experience with a data science problem of my choosing and to learn how to effectively apply machine learning algorithms in the real world. My goal is to create an application that can accurately predict where students need tutoring based on their past grades. This project will require me to use various classes of statistical models, such as regression, decision trees, and neural networks. 

How to Write a Personal Statement for Masters Programme in Data Science?

If you are looking for the best way to write a sample personal statement for a master in data science, you should follow these steps: 

• Step 1: The first step is to find out what courses are available in your area and how long it takes to complete them. You can find this information on websites online. 
• Step 2: Once you have this information, you need to think about how much time you will have available each day. It is important that you do not leave your studies until you finish all of your courses because once you finish your degree program, there will be no more work available for you. Your ability to continue working will depend upon how well your personal statement for data science courses was received by universities and whether or not they offer scholarships for those who want to study abroad or online. 
• Step 3: In order to write a good personal statement for M.Sc data science, you will need to think about why you want to continue your education after completing your bachelor's degree program. This could be because of what happened during college or because of something else entirely (such as family obligations). If it is something that happened during college, then you will need to explain what that event was and how it has affected your desire to continue your education. If it is something that happened outside of college, then you should talk about how that event impacted your academic performance and why you want to continue studying.

Data Science Personal Statement Example 

Following is a data science personal statement example. You can refer to this data science statement of purpose example and keep in mind the necessary points.

Source: personal-statement-examples.com

Tips to Write an Effective Data Science Personal Statement

The following tips will help you write an effective personal statement for a master in data science: 

1. Use a Template

It's best to use a template that has been created by experienced admissions officers and other professionals in the field. This means you can skip the writing process entirely since they've already done most of it for you. 

2. Keep Your Sentences Short and Simple

Your goal should be no more than one or two paragraphs per section (including your application summary), which means keeping your sentences as short as possible without compromising clarity or coherence. If there are too many adjectives or numbers used in an otherwise simple sentence, try replacing them with action verbs like "ran" instead of "ran fast." 

3. Avoid Clichés

In your data science personal statement sample, instead of saying things like "I am dynamic," try saying something more descriptive such as “I am highly dynamic” instead because this shows off how creative your mind works while also showing off how well-rounded personas are important traits needed by anyone working at companies when writing an M.Sc data science personal statement.  

Do’s and Don’ts While Writing Personal Statement

Data science is a booming field with a lot of opportunities. You can work anywhere and make a good salary with this skill. If you think that it’s not for you, then it’s time to think again. The world has changed and so have our needs as individuals. Data science professionals will be needed in the future because of their role in shaping our lives as we know them today. In order to pursue a career in this broad field of data science, it is recommended that you pursue KnowledgeHut to learn its principal aspects and gain in-depth knowledge about data science. Data Science Courses to learn its principal aspects and gain in-depth knowledge about data science.

Frequently Asked Questions (FAQs)

Find out what diploma courses are available in your area and how long it takes to complete them. Once you have this information, you need to think about how much time you will have available each day. After evaluating all these things, start writing your personal statement using templates. 

• The reason(s) why you selected this subject(s) 
• Your chosen area of study and how it relates to the current studies 
• Your experiences in relation to your chosen subject(s) 
• What are your interests and responsibilities in relation to the subject you are studying? 
• After university, what's next? 
• A summary of why you will make an excellent student 
• Don’t use quotes 
• Don’t let spelling and grammatical errors spoil your statement. 
• Don’t copy and paste 

During the writing of the letter of intent for the MS in Data Science course, it is important to take into account the basic questions asked by the institution, including what kind of ambitions the prospective candidate has and the inspiration behind those ambitions. If the students do not want to sound conversational in their essays, then they should keep in mind that the tone should be formal instead of informal.

Ashish Gulati

Ashish is a techology consultant with 13+ years of experience and specializes in Data Science, the Python ecosystem and Django, DevOps and automation. He specializes in the design and delivery of key, impactful programs.

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How To Write An Appealing Personal Statement For Masters Programme In Data Science

Illustration by How To Write An Appealing Personal Statement For Masters Programme In Data Science

• Published on July 31, 2020
• by Sejuti Das

Besides submitting test scores, recommendation letters, and an undergraduate transcript, one essential requirement of applying to a data science masters programme is the application essay — aka personal statement. The personal statement is where applicants need to convince the professors their ability and worth of getting selected in the master programme . 

In fact, many a time, a personal statement acts as a deciding factor for getting chosen for a prestigious masters programme in the field of data science . Thus, one needs to be extremely cautious while writing a personal statement for their master’s application. Not only does it help the university authorities determine the sincere interest of the applicant to enrol for the course, but also provide a chance to the students to stand out of the crowd highlighting their skills and relevancy.

Having said that, data scientists are experts in mathematics, but writing might not always be their expertise , and a personal statement is usually longer than you think and requires to be well crafted in order to grab the attention of professors and administrators. So, if decided to pursue higher studies in the data science field and have narrowed down universities to apply, this article can help you write a winning personal statement required to apply for the data science masters’ programme.

Also Read: The 10 Most Promising Data Science Masters Programs In US

Planning Is The Key: Highlight The Reason To Study Data Science Masters

Although it is stated as ‘personal,’ a personal statement doesn’t require applicants to share the intimate details of their life; instead, it needs to highlight the intention of the applicant for the particular master’s programme. To avoid any confusion or mistakes, the first step to write a personal statement for a data science masters programme is to brainstorm around it and plan it before actually starting to write. It is critical to make notes and use bullet points when planning, which can later be referred to while writing the personal statement. One should research thoroughly about the course requirements and the university, and prepare a list of their achievements and goals that can come handy while writing the essay. 

Most universities expect their applicants to adhere to a specific word limit for the personal statement, and thus a good brainstorming will help applicants to keep their essay relevant and to the point. Planning will help in setting the context, creating a structure and forming a narrative of the piece that is critical for drafting a compelling statement.

Also Read: What Not To Include In Your Data Science Resume

Have A Killer Intro & A Concise Conclusion: Relevant To The Passion For The Field

An attention-grabbing intro and a hard-hitting conclusion are again critical for writing a compelling personal statement. The first paragraph can create the first impression of the applicant in front of the professors, and a sharp end will help them remember that candidate among the crowd. The readers of the personal statement are the experts from the data science industry and academics; thus, they expect the writeup to be extremely intriguing in terms of content. 

Personal statements are usually lengthy but require to be extremely clear in sending out the message. Rather than starting the essay with some cliches, data science applicants should begin their personal statement highlighting their passion for the stream and their domain proficiency. And to have a definite ending, these data scientists must ensure to convey their genuine interest in pursuing the master’s programme, and how their skills are relevant to the stream.

Also Read: Tips And Templates For A Data Scientist Resume

Be A Good Story Teller: Highlight Experiences & Skill Sets

Thirdly, data science applicants must showcase their skill sets and experience in their personal statements without repeating the information that is already mentioned in their application form. And that’s why it is critical to be a good storyteller with their statement, where applicants can highlight their skills by talking about a particular data science research project that helped in solving real-life problems. One can also point out their experiences, knowledge, and quantify their expertise in the field that can help them in pursuing further studies.

The job of the personal statement is to let the administrators and professors know the abilities of the applicants to be qualified for the master’s programme. Data scientists can also mention their thesis, publications, journals or any relevant activities that can help them in getting selected. A well crafted personal statement avoids clichés, jargons, and too many details, and should be presented formally with a clear narrative.

Also Read: How To Create A Compelling Cover Letter To Land A Data Science Job

Focus On Your Domain & The Programme

Unlike undergraduate courses, masters programmes are more specific as well as require applicants to understand the domain they are pursuing. Consequently, while writing a personal statement, one needs to sync their interest according to the requirement of the programme and emphasise on the specific skills that match the area of expertise. One can also network with relevant faculty members and seniors to get a better understanding of the requirements of the program.

Many universities are also working on several ongoing data science projects, citing one of them corresponding to the interest, can also be a great addition to the personal statement. Furthermore, applicants can also write about what inspired them to pursue this particular domain and how their work will contribute to the field. One can also share their personal experiences and how that has helped in pursuing this course.

Also Read: What Data Science Graduates Need To Do To Get Hired During Covid-19

Don’t Be Generic: Customise The Write Up For The Course

Lastly, it is critical that the essay is unique and thus requires to be customised according to the university and its requirements. Applicants don’t have to start from scratch every time they are applying to a university, but they must ensure that they still provide a unique draft personal statement to each application. Professors and administrators read thousands of personal statements in a day, and therefore to be unique, applicants cannot pick up generic content to build their essay.

Applicants can also make the personal statement unique by adding up personal experiences relevant to the field, which will not only make the read interesting but also will allow the readers to empathise with the applicant. One can also add up a few of their failures to make it sound genuine as well as relatable. Usually, masters programmes don’t conduct face to face interviews; thus, personal statement plays a vital role in the applicants’ admission process.

Also Read: 10 Commonly Asked Puzzles In A Data Science Interview

Other Things To Keep In Mind

• Personal statements are not university applications, so don’t be repetitive.
• Highlight why this university is the right choice for the career you are planning to pursue.
• Although it’s the life experiences one shares in their personal statements, it indeed requires to be professional and to the point. 
• Avoid grammar, spelling, and punctuation errors.

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Guide to Writing Data Science Personal Statements

Table of Contents

A  data science personal statement  is an integral part of the application process for aspiring data scientists. It provides recruiters and admissions board representatives insight into a candidate’s motivations, skills, and abilities related to their chosen field of study. 

The statement should demonstrate a clear understanding of the concepts and practices that make up the data science discipline. It showcases an applicant’s technical aptitude and professional experience. A successful personal statement will convey passion for the profession through emotionally resonant language and examples. 

Personal statements are everyday encounters in job applications as well as applications to special programs and postgraduate studies.

While personal statements and resumes both demonstrate an applicant’s qualifications, the former does so in paragraph form. This is crucial because it allows applicants a reasonable degree of creativity to create vivid depictions and powerful messages.

This allows them to not only create a good impression on readers but also to evoke emotions.

The Importance of a Personal Statement

The primary function of a personal statement is to give insight into the type of person you are. It provides recruiters and admissions board officers a glimpse into your qualifications . 

The actual value of a personal statement lies in its exposition. While resumes and summaries give readers the information they need pertaining to your qualifications, personal statements have a more intimate feel.

They read like stories. They take readers on a journey that helps them fully appreciate an applicant’s skills, experience, and character. Personal statements are particularly beneficial because they encourage recruiters and admissions board members to see candidates as more than just their qualifications. They are a way to show evaluators the person behind the application.

But, as good as all these sound, you can reap these benefits only through a compelling personal statement. If you’re unsure of how to write your data science personal statement, heed the following tips.

Tips for Writing a Data Science Personal Statement

Highlight Your Most Relevant Experience

Demonstrate your skills and accomplishments in data science by including concrete examples. Include experiences such as projects you have worked on or organizations/industries in which you have experience. Doing so will help to demonstrate that you possess the necessary qualifications for a successful career in data science. 

Showcase Personal Passion

Showcasing your passion for data science. You can do this by highlighting the personal challenges, successes, and motivations which led to your interest in the field. Explain what inspired you and how this has driven you to pursue further education and, ultimately, a career in data science. 

Be Specific

Make sure that when describing both experiences and achievements, they are as specific as possible.

Doing so will allow an admissions panel to better understand the nature of your work and its relevance to data science. Providing evidence to support statements (e.g., screenshots, code snippets, sample analyses) is also beneficial. 

Use Clear Language

Being clear and concise is essential when writing about complex topics like data science.

Aim to use language which conveys your points without overcomplicating them with jargon or technical terms. This will make it easier for an admissions panel to understand your application, increasing the chances of being accepted onto their program. 

Leverage Emotional Writing

The tone of your statement should reflect a human quality, using emotions and speaking authentically about why data science excites you. If appropriate, include colloquial language throughout; while ensuring it does not detract from the overall clarity of your essay.

Data Science Personal Statement Example

I have been deeply invested in the burgeoning field of data science for almost a decade. My expertise has allowed me to explore its nuances and applications with avid enthusiasm. I utilized my specialized knowledge to contribute significantly to many successful projects. As a result, I have accrued an immense portfolio of experience. My experience ranges from predictive analytics to natural language processing. This sets me apart as a leader in a rapidly-evolving industry.

From analyzing complex datasets to constructing scalable machine learning systems, my tenaciousness drives me to continually seek out dynamic challenges. Although I am thoroughly versed in all theoretical aspects of data science, I thrive on uncovering new possibilities through experimentation and creative problem-solving. I pride myself on being able to translate technical jargon into actionable solutions. 

A personal statement is a short paragraph that outlines a candidate’s skills, experiences, and motivation . It is an essential document because it allows applicants to connect with readers and establish a good impression. Remember our simple tips. While they won’t make you an expert overnight, they will help you cement good writing habits that will serve you well in the future.

Abir Ghenaiet

Abir is a data analyst and researcher. Among her interests are artificial intelligence, machine learning, and natural language processing. As a humanitarian and educator, she actively supports women in tech and promotes diversity.

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Personal Statement that got selected to MS in Data Science, University of Pennsylvania (UPenn)

Penn’s Master of Science in Engineering (MSE) in Data Science prepares students for a wide range of data-centric careers, whether in technology and engineering, consulting, science, policy-making, or understanding patterns in literature, art or communications.

It blends leading-edge courses in core topics such as machine learning, big data analytics, and statistics, with a variety of electives and an opportunity to apply these techniques in a domain specialisation – a depth area – of choice.

So, what does it take to get into one of the top 15 programs of the USA in Data Science? I mean, look at it! Wouldn’t you want to spend 2 years here?

So, let’s look at the ‘Personal Statement’ requirements what the UPenn lists out in its Admission Requirements:

• No more than two pages in a readable font/size:
• Why are you interested in this program?
• What have you done that makes you a great candidate?
• How will you benefit from the program?
• How do you plan to contribute to the student community in SEAS while you’re here?
• Why will you succeed in the program?
• What will you do/accomplish once you have completed the program?

As it is amply clear, the AdCom doesn’t want the details of EVERYTHING that you have done in your academic projects. You should answer only these 6 questions, in a way that best justifies your interest in this program. Right?

Here is where the Mridul got it wrong.

About Mridul

Mridul grew up in Mumbai, went to KJ Somaiya College Of Engineering in Mumbai, and had a GPA of 8.46.

He had a GRE score of 322 (167 Q 155 V) and a TOEFL score of 103.

His academic projects reasonably aligned with the research work at UPenn, one of his dream schools.

When he sent us the first draft, it was his entire story of all the things he has done till now. In total, it was 4 PAGES LONG!

So, our first revision was to cut short the massive piece of self-appreciation, to a workable draft of around 1000 words.

Then, we cherry picked some of the most notable projects of Mridul, and tried to address the questions that the AdCom was really looking for.

After 3 rounds of revision, we arrived at the final draft which looked like this:

As it can be seen, each paragraph of Mridul’s Personal Statement, tries to address a question which helps the AdCom to decide if you are the ‘RIGHT FIT’ for the class.

Since there was no hard limitation on the number of words, we stuck to around 1100 words to clearly and concisely tell Mridul’s story to the AdCom.

Mridul was accepted to three graduate programs – University of Pennsylvania (MS in Data Science), University of California Irvine (MS in Computer Science), and CMU (MS in Data Science)

We couldn’t be happier! Like this happy puppy.

Read Shrishti’s application journey to MS in Computer Science, University of Southern California (USC)

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Home / Data Science Programs / Best Master’s in Data Science Programs / Statement of Purpose

How to Write a Statement of Purpose for Master’s in Data Science

Many colleges and universities require a statement of purpose for master’s in data science student applications. The statement of purpose can play an important role in your application, as it allows admissions staff to learn about your goals, experience and education outside of scores and grades. This guide will cover what a statement of purpose is, what needs to be included in it, frequently asked questions and tips to help craft your own.

What Is a Statement of Purpose for Master’s in Data Science?

A statement of purpose is a short essay written by master’s of data science applicants discussing their work and educational history, goals for the program and future career interests. A statement of purpose for master’s in data science programs may also detail any deficiencies in an application such as an employment gap, low GRE or GMAT test scores or grades and information about independent study in lieu of other relevant coursework. The statement of purpose provides a space to highlight your specific life experiences and goals in your own words.

What Is the Admissions Committee Looking for in Your Application?

Admissions committees typically look for the following information:

• Who is applying?  What about the student’s academic or personal background, work experience or extracurricular activities stands out? Does the applicant show a history of demonstrated interest in data science? What will they be able to add to a graduate program environment?
• Does the applicant have analytical skills or experience?  Data science requires a person to deeply analyze large and complex data sets. While some core capacities, like mathematics, may be taught, a statement of purpose provides a space to demonstrate analytical skills or relevant experience.

Statement of Purpose Format Requirements

While every school has different requirements, the general format for a data science master’s statement of purpose may include:

• Length: 1-2 pages; school will specify length.
• Word Count: 250-500 words; some schools allow up to 1,000 words.
• Spacing: Double or single spaced
• Font: Times New Roman in 12-point font
• Margins: No less than 1 inch
• Format: Microsoft Word (.doc, .docx) or PDF format

Refer to the college or university’s requirements before submitting, particularly if you are sending out multiple statements of purpose to different schools.

Statement of Purpose vs. Personal Statement

Master’s in data science programs may ask for a statement of purpose or a personal statement—some may ask for both. While these might seem like the same thing, there are a few distinctions.

A statement of purpose typically is focused on academic and analytical information. A school requesting a statement of purpose may request information about reasons for applying for graduate study as well as relevant professional interests and goals. A personal statement might be a broader essay asking about life experiences and interests—though still as they relate to the program.

It’s important to read admissions requirements carefully to determine what information each school wants from either a statement of purpose or a personal statement.

10 Tips for Statement of Purpose for Data Science Programs

A statement of purpose may be daunting for master’s in data science applicants, but there are some steps you can take to make sure you’re delivering a good effort. The tips below can help guide you while writing your statements of purpose for data science programs.

Read Examples of Statements of Purpose for Data Science

Read samples of statements of purpose. If you have access to successful applicants’ essays, read them. If not, read a wide variety of statements of purpose and notice what does and does not work. Be sure not to plagiarize as it could be grounds to deny your application.

Brainstorm Topics and Decide on a Structure

As mentioned above, a statement of purpose should highlight who you are and how you work analytically. Take time to brainstorm relevant topics that showcase experience as well as signs of interest in the data science field. After you have your bullet points set, focus on a structure that best highlights you as an applicant. Make an outline before you start writing.

Pick One or Two Narrow Topics and Stay Focused

A statement of purpose should be clear and to the point. It’s not a recap of your entire life or resume. Avoid covering too much information in your statement of purpose. Stay focused on one or two key topics and provide plenty of supporting information to showcase your analytical skills as it relates to those points.

Make Your First Paragraph Interesting

Admissions committees read hundreds of applications. A focused and interesting introductory paragraph can grab the attention of the reader and keep them from putting your statement down. A personal anecdote, a thought-provoking question or an emotionally compelling story at the beginning of your statement of purpose can all grab a reader’s attention.

Highlight Information That Sets You Apart

Write about any activity that highlights your strengths as a data scientist. If you have relevant experience on a resume or affiliations with a professional organization, make sure you highlight that. A statement of purpose, in part, is about what makes you qualified to  become a data scientist .

Keep the Focus on YOU

A statement of purpose is about how your experience, culture and background has helped prepare you for a career in data science. This is not the time to write at length about your professor’s career or general concepts of data science. A statement of purpose often requires a limited amount of space. Make sure you are using it effectively to highlight your own strengths.

Be Yourself and Don’t Fake Experience

Take the truthful approach and recall your experiences and accomplishments with complete honesty and authenticity. While it may be tempting to inflate your experience or accomplishments in data science or analysis, misrepresenting data—or outright lying—will hurt more than it will help.

Keep Language Concise and Tone Positive

Data science is used to draw information from raw data sets and as such, those working in data science may need to be able to explain their findings. A statement of purpose is the first place you can showcase an ability to effectively communicate. Avoid rambling, vague or repetitive language and keep the tone positive and outcome-focused.

Double Check Schools’ Instructions

Read and re-read the school’s instructions for submitting a statement of purpose. Data science requires attention to detail. You don’t want to disqualify yourself by not following basic instructions. Make sure you meet all the stated requirements, and don’t make mistakes like exceeding word count or incorrectly formatting a document.

Proofread, Proofread and Proofread

Check your essay for any grammatical errors. While data scientists often deal with numbers more than writing, it’s still important to proofread because it will show the admissions committee you pay attention to details.

FAQs About Data Science Statements of Purpose

Before beginning your master’s in data science application, get answers to any final questions about statements of purpose. If you’re still unsure about the process, consider asking your admissions counselor.

Take the statement of purpose seriously. Often, it is the only part of your application where the admissions committee gets to hear directly from you. A well-crafted statement of purpose can help provide context around low test scores or grades as well as highlight how your experience has helped prepare you for the program.

Whether applying to a campus-based or  online master’s in data science , it’s better to start working on your statement of purpose earlier to ensure you have sufficient time to think and prepare. Since some master’s in data science programs may have rolling application and start dates, it’s best to double check admissions deadlines and make sure you have plenty of time to write and edit your statement of purpose.

Schools may have different requirements for statement of purpose submissions. Check directly with your school of interest. In general, keep statements of purpose concise—word counts may range from 250 to 1,000 words—and focused on academic and professional achievements that may help you succeed in a data science program.

Different schools have different word count requirements. Some schools will specify the length, but others do not. In general, a statement of purpose is between 300 and 500 words. Some schools allow up to 1,000 words. If word count isn’t explicitly stated, try to be concise. These are short essays. Writing a statement of purpose is one of the first steps toward studying and working in data science. If you want to better prepare for your application, it’s best to start searching for programs early to understand their requirements. Students can either look at  data science programs by state  or consider  data science scholarships available  for students.

Last updated: March 2022

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How to Write a Personal Statement for a PhD Program Application

Personal statement guidelines, general guidelines to keep in mind:.

• One size does not fit all : Tailor your personal statement to each program and department you are applying to. Do your research to learn what is unique about each of your choices and highlight how this particular program stands out.
• Yes, it’s personal : Showcase your unique strengths and accomplishments. Explain what influenced your personal decisions to pursue the program. Ask yourself, could this be applied to your friend or neighbor? If so, you need to be more specific and provide examples. Saying that you are a “good scientist” isn’t enough. Provide examples of your previous research experience, projects you’ve completed, and what technical skills you learned. Explain how you overcame any challenges along the way.
• Set aside enough time :  Although personal statements are generally short in length (approx. 700 words; 1-2 pages), give yourself ample time to write a strong, well-written statement. It takes more time than you think to develop a final draft for submission.
• Focus on your spelling, grammar, and vocabulary :  It’s important to present a well-written statement with good grammar and vocabulary. Write concrete, succinct sentences that flow well. Avoid flowery language. Visit the  Writing Center  for additional review and feedback.
• Proofread one more time:  Check your grammar and spelling again before submitting your final draft. Ask a friend, professor, or advisor to proofread your final draft one more time before sending it in. 

YOUR PERSONAL STATEMENT SHOULD ANSWER THE FOLLOWING QUESTIONS:

• Why do you want to complete further research in this field?  Write down a list of reasons as to why you are interested in pursuing further study in the field. When did you become interested in the field and what knowledge have you gained so far? Describe how your previous work provided the foundation and for further study.
• Why  have you  chosen to apply to this particular university ? Does the institution have a particular curriculum, special research facilities/equipment, or interesting research that appeal to you?
• What are your strengths ? Demonstrate how you stand out from other candidates. Highlight relevant projects, dissertations thesis or essays that demonstrate your academic skills and creativity. Include IT skills, research techniques, awards, or relevant traveling/ study abroad experience.
• What are your transferable skills?  Be sure to emphasize transferable skills such as communication, teamwork, and time management skills. Give examples of how you have demonstrated each of these with specific examples.
• How does this program align with your career goals?  It’s okay if you don’t know the exact career path you plan to take after completing your PhD. Provide an idea of the direction you would like to take. This demonstrates commitment and dedication to the program.

ADDITIONAL RESOURCES

For examples of successful personal statements, visit the  Online Writing Lab (OWL) .

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Sample Personal Statement Data Science and Analytics

by Talha Omer, MBA, M.Eng., Harvard & Cornell Grad

In personal statement samples by field.

The demand for data science experts is increasing in every industry, not just in technology. Moreover, it is a high-paying job with a guaranteed placement even before graduation. Hence, the competition is also increasing, and with every passing year, the ease of getting into a top data analytics program keeps getting harder. So, start early with your application and make sure you put good time into drafting your perfect application essays.

Here is a sample personal statement of data science professional with two years of experience working in a big data consulting firm. This candidate was able to secure admission into top data science programs like Vanderbilt and CMU. He has graciously shared his successful essay so that prospective applicants can benefit from it.

Related Personal Statements 1) Sample Personal Statement Business Analytics 2) Sample Personal Statement in Advanced Analytics (admitted to NCSU) 3) Sample Personal Statement in Analytics (admitted to Georgia Tech) 4) Sample Personal Statement in Management and Analytics (admitted to LBS)

Sample Personal Statement for Big Data/Data Science/Data Analytics

I want to play a critical role as a big data architect who translates business problems into solvable analytics. In the short run, I want to work for a leading FMCG firm like Unilever, P&G, or Nestle and define procedures and models to determine what IT systems gather and remove information silos across different departments. In the long run, however, I want to extend my expertise in the public sector and advise corporates and governments alike across the globe to solve several social and business problems through big data.

My undergraduate has equipped me with extensive quantitative knowledge and technical experience around different themes in Computer Engineering. I’ve focused most of my studies on GUI in C++, apps and game development, and intensive numerical analysis. This was further honed when I joined Afiniti Experience Ltd as Software Engineer.

I have written scripts using MySQL and MSSQL to process large datasets and troubleshoot and configure the company’s operations. At Afiniti, I have developed a strong skillset in collecting, storing and managing big data. I plan to translate business problems into analytics-driven solutions, which I would embed into business operations. However, I must first curate my leadership skills and polish my skillset in designing computational pipelines for high-dimensional and large-scale complex data.

At Vanderbilt, I want to develop my theoretical basis of operations and decision technologies which ideally dovetails with my career interests of applying quantitative techniques in business operations. Beyond the classroom, I would greatly appreciate the opportunity to learn from and collaborate with Vanderbilt’s influential faculty. The Data Science Institute will allow me to learn data-driven research and train me as a future leader.

In particular, the techniques of Gautam Biswas on learner modeling and adaptivity are foundational for my current work. Moreover, Jeffrey D. Blume’s expertise in statistical inference and methodology for analyzing and interpreting receiver operating characteristic curves will equip me with tools through which I can excel in my future career.

My future aspirations require strong leadership qualities recognized in a data-driven world. For this purpose, I would greatly benefit from Data Science Institute’s capstone development and lead a project from scratch. This will mold my personality into a global leader’s persona.

Lastly, I will exploit the locational advantage of living at Vanderbilt and gain access to multiple fortune 500 companies where I can seek pro bono consulting opportunities and enhance my problem-solving acumen. I am also confident in acquiring the necessary communication skills to present solutions to Product Managers, Sales Associates, Engineers, and Marketing Teams.

To sum up, owing to my aspirations and professional expertise in big data synthesis, I am confident of using the vibrant opportunities at Vanderbilt’s master’s in data science and converting it into an ideal segue for my future career aspirations.

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Data science personal statement example.

Ever since the commencement of high school studies, I was keen to know application of mathematics in factuality. Its abstract nature intrigued me to question my teachers about relevance and usefulness to mankind. I wanted to apply my learning and understanding invariably in real world circumstances.

It was until the introduction of Operations Research, while studying at college, which satiated my yearning to a certain extent. The problem solving and analytical techniques in Operations Research fostered the logic and decision making, which I believe, is one key component for developing models in real world or an approach towards mathematical modeling.

The process of creating mathematical representation of a real-world scenario to make predictions or provide insights captivated my interest. Although real world problems are often open ended and require iterative methods, but would also promote problem solving skills, creativity and innovation.

Besides Math, my interest in computing initiated right while coding the first program in C++ during bachelors. The backend scripting while using mobile phone, social media, scanning barcode at grocery or making online transactions, escalated my enthusiasm. I believed in the vigorous nature of programming and its effectiveness to engage world dynamically.

Also the symbiotic relation of computing and mathematics led me towards researching pathways blending the two disciplines, to evolve more powerful outcomes which would inherit the scientific and analytic approaches. While discussing it with a friend last year, I got introduced to the big data world and the interdisciplinary field of Data Science, combining aspects of statistics, mathematics, programming and domain expertise to address real problems. I was looking forward to traverse a similar realm and hence Data Science receives preference.

My previous studies helped to gain essential strategic and adaptive reasoning in the study of Algebra, Geometry, Statistics and Calculus. Integration of mathematics with computing widens the scopes and facilitates challenging yet interesting opportunities. This has instilled passion in me to explore computing specializations like Algorithms, Data structures and Programming fundamentals.

For the past six months I have been working diligently, enrolled in several courses to learn programming fundamentals with Python, SQL basics, Foundations of Data Science, k-Means clustering in Python and also Machine Learning concepts on self-learning platforms like Coursera, Udemy, Simplilearn and Youtube. Successful execution of programs like Conversion scales, time zones, board game and DNA processing using Python, exhilarated me and imparted encouragement. Although this helped me immensely to acquire foundational understanding of the subject. However, I needed more holistic education to gain mastery by pursuing formal studies and enrolling in university.

I started looking for reputed universities to pursue masters in Data science or related computer science streams. I figured that the role of data scientist is one of the most in-demand jobs currently in UK and US. Most likely its demand will originate in other regions of the world. My preference towards UK was obvious for couple of reasons. One year master’s program itself is an advantage from an international student perspective. Ever since inception, British universities are known for quality education and accreditation across the world. Many prominent world personalities from all walks of life, have graduated from English universities.

Joining on campus program at foreign land is much more than just universities. It is about the place, environment, people and also the facilities prevailing. As an expatriate living in Saudi Arabia, for about ten years, I have learnt this significantly. Cities like London, Birmingham, Manchester and Leeds provide residence to several expatriate communities exhibiting diverse vibrant cultures.

The world has reached a stage when every conceivable organization is becoming data-driven. Like the vast and ever-expanding universe, the big data fields are in a perpetual expansion mode, both fascinate me. Data is becoming more valuable in fast-paced life and this is creating a plethora of opportunities for data-centric roles in reputed organizations. It is no exaggeration to state that Data Science is making astonishing progress in the multiple domains of technology, economy, commerce and medicine.

After completing masters, I look forward to join established organization to acquire mastery and gain hands on experience in Data Science. However, time ahead, I would like to start a company where I can design advance models with the acquired knowledge and expertise from all the domains. For instance model like – ‘Accident free zones’ by collecting information from traffic flow, speed, regulations to make informed decisions regarding public safety or a ‘model school’ to be implemented by combining the best from several curriculums, adaptable for future generations.

For the past ten years I have been in the field of education, gaining expertise in teaching mathematics, designing curriculums and mentoring learning community. Although teaching-learning is my passion, and would definitely continue it as a hobby, however I am also a kind of person who believe in constant change and progress in life. This instinct supports me to accept demanding expeditions. My future endeavors would be to take slight detour from my current profession to establish myself in another exciting province, to leverage my knowledge, skills and career.

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Sell yourself and your science in a compelling personal statement

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Personal statements — essays highlighting personal circumstances, qualities and achievements — are used extensively in science to evaluate candidates for jobs, awards and promotions. Five researchers offer tips for making yours stand out in a crowded and competitive market.

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Gre prep online guides and tips, 3 successful graduate school personal statement examples.

Looking for grad school personal statement examples? Look no further! In this total guide to graduate school personal statement examples, we’ll discuss why you need a personal statement for grad school and what makes a good one. Then we’ll provide three graduate school personal statement samples from our grad school experts. After that, we’ll do a deep dive on one of our personal statement for graduate school examples. Finally, we’ll wrap up with a list of other grad school personal statements you can find online.

Why Do You Need a Personal Statement?

A personal statement is a chance for admissions committees to get to know you: your goals and passions, what you’ll bring to the program, and what you’re hoping to get out of the program.  You need to sell the admissions committee on what makes you a worthwhile applicant. The personal statement is a good chance to highlight significant things about you that don’t appear elsewhere on your application.

A personal statement is slightly different from a statement of purpose (also known as a letter of intent). A statement of purpose/letter of intent tends to be more tightly focused on your academic or professional credentials and your future research and/or professional interests.

While a personal statement also addresses your academic experiences and goals, you have more leeway to be a little more, well, personal. In a personal statement, it’s often appropriate to include information on significant life experiences or challenges that aren’t necessarily directly relevant to your field of interest.

Some programs ask for both a personal statement and a statement of purpose/letter of intent. In this case, the personal statement is likely to be much more tightly focused on your life experience and personality assets while the statement of purpose will focus in much more on your academic/research experiences and goals.

However, there’s not always a hard-and-fast demarcation between a personal statement and a statement of purpose. The two statement types should address a lot of the same themes, especially as relates to your future goals and the valuable assets you bring to the program. Some programs will ask for a personal statement but the prompt will be focused primarily on your research and professional experiences and interests. Some will ask for a statement of purpose but the prompt will be more focused on your general life experiences.

When in doubt, give the program what they are asking for in the prompt and don’t get too hung up on whether they call it a personal statement or statement of purpose. You can always call the admissions office to get more clarification on what they want you to address in your admissions essay.

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What Makes a Good Grad School Personal Statement?

A great graduate school personal statement can come in many forms and styles. However, strong grad school personal statement examples all share the same following elements:

A Clear Narrative

Above all, a good personal statement communicates clear messages about what makes you a strong applicant who is likely to have success in graduate school. So to that extent, think about a couple of key points that you want to communicate about yourself and then drill down on how you can best communicate those points. (Your key points should of course be related to what you can bring to the field and to the program specifically).

You can also decide whether to address things like setbacks or gaps in your application as part of your narrative. Have a low GPA for a couple semesters due to a health issue? Been out of a job for a while taking care of a family member? If you do decide to explain an issue like this, make sure that the overall arc is more about demonstrating positive qualities like resilience and diligence than about providing excuses.

Specific Examples

A great statement of purpose uses specific examples to illustrate its key messages. This can include anecdotes that demonstrate particular traits or even references to scholars and works that have influenced your academic trajectory to show that you are familiar and insightful about the relevant literature in your field.

Just saying “I love plants,” is pretty vague. Describing how you worked in a plant lab during undergrad and then went home and carefully cultivated your own greenhouse where you cross-bred new flower colors by hand is much more specific and vivid, which makes for better evidence.

A strong personal statement will describe why you are a good fit for the program, and why the program is a good fit for you. It’s important to identify specific things about the program that appeal to you, and how you’ll take advantage of those opportunities. It’s also a good idea to talk about specific professors you might be interested in working with. This shows that you are informed about and genuinely invested in the program.

Strong Writing

Even quantitative and science disciplines typically require some writing, so it’s important that your personal statement shows strong writing skills. Make sure that you are communicating clearly and that you don’t have any grammar and spelling errors. It’s helpful to get other people to read your statement and provide feedback. Plan on going through multiple drafts.

Another important thing here is to avoid cliches and gimmicks. Don’t deploy overused phrases and openings like “ever since I was a child.” Don’t structure your statement in a gimmicky way (i.e., writing a faux legal brief about yourself for a law school statement of purpose). The first will make your writing banal; the second is likely to make you stand out in a bad way.

Appropriate Boundaries

While you can be more personal in a personal statement than in a statement of purpose, it’s important to maintain appropriate boundaries in your writing. Don’t overshare anything too personal about relationships, bodily functions, or illegal activities. Similarly, don’t share anything that makes it seem like you may be out of control, unstable, or an otherwise risky investment. The personal statement is not a confessional booth. If you share inappropriately, you may seem like you have bad judgment, which is a huge red flag to admissions committees.

You should also be careful with how you deploy humor and jokes. Your statement doesn’t have to be totally joyless and serious, but bear in mind that the person reading the statement may not have the same sense of humor as you do. When in doubt, err towards the side of being as inoffensive as possible.

Just as being too intimate in your statement can hurt you, it’s also important not to be overly formal or staid. You should be professional, but conversational.

Graduate School Personal Statement Examples

Our graduate school experts have been kind enough to provide some successful grad school personal statement examples. We’ll provide three examples here, along with brief analysis of what makes each one successful.

Sample Personal Statement for Graduate School 1

PDF of Sample Personal Statement 1 – Japanese Studies

For this Japanese Studies master’s degree, the applicant had to provide a statement of purpose outlining her academic goals and experience with Japanese and a separate personal statement describing her personal relationship with Japanese Studies and what led her to pursue a master’s degree.

Here’s what’s successful about this personal statement:

• An attention-grabbing beginning: The applicant begins with the statement that Japanese has never come easily to her and that it’s a brutal language to learn. Seeing as how this is an application for a Japanese Studies program, this is an intriguing beginning that makes the reader want to keep going.
• A compelling narrative: From this attention-grabbing beginning, the applicant builds a well-structured and dramatic narrative tracking her engagement with the Japanese language over time. The clear turning point is her experience studying abroad, leading to a resolution in which she has clarity about her plans. Seeing as how the applicant wants to be a translator of Japanese literature, the tight narrative structure here is a great way to show her writing skills.
• Specific examples that show important traits: The applicant clearly communicates both a deep passion for Japanese through examples of her continued engagement with Japanese and her determination and work ethic by highlighting the challenges she’s faced (and overcome) in her study of the language. This gives the impression that she is an engaged and dedicated student.

Overall, this is a very strong statement both in terms of style and content. It flows well, is memorable, and communicates that the applicant would make the most of the graduate school experience.

Sample Personal Statement for Graduate School 2

PDF of Sample Graduate School Personal Statement 2 – Musical Composition

This personal statement for a Music Composition master’s degree discusses the factors that motivate the applicant to pursue graduate study.

Here’s what works well in this statement:

• The applicant provides two clear reasons motivating the student to pursue graduate study: her experiences with music growing up, and her family’s musical history. She then supports those two reasons with examples and analysis.
• The description of her ancestors’ engagement with music is very compelling and memorable. The applicant paints her own involvement with music as almost inevitable based on her family’s long history with musical pursuits.
• The applicant gives thoughtful analysis of the advantages she has been afforded that have allowed her to study music so extensively. We get the sense that she is insightful and empathetic—qualities that would add greatly to any academic community.

This is a strong, serviceable personal statement. And in truth, given that this for a masters in music composition, other elements of the application (like work samples) are probably the most important.  However, here are two small changes I would make to improve it:

• I would probably to split the massive second paragraph into 2-3 separate paragraphs. I might use one paragraph to orient the reader to the family’s musical history, one paragraph to discuss Giacomo and Antonio, and one paragraph to discuss how the family has influenced the applicant. As it stands, it’s a little unwieldy and the second paragraph doesn’t have a super-clear focus even though it’s all loosely related to the applicant’s family history with music.
• I would also slightly shorten the anecdote about the applicant’s ancestors and expand more on how this family history has motivated the applicant’s interest in music. In what specific ways has her ancestors’ perseverance inspired her? Did she think about them during hard practice sessions? Is she interested in composing music in a style they might have played? More specific examples here would lend greater depth and clarity to the statement.

Sample Personal Statement for Graduate School 3

PDF of Sample Graduate School Personal Statement 3 – Public Health

This is my successful personal statement for Columbia’s Master’s program in Public Health. We’ll do a deep dive on this statement paragraph-by-paragraph in the next section, but I’ll highlight a couple of things that work in this statement here:

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• This statement is clearly organized. Almost every paragraph has a distinct focus and message, and when I move on to a new idea, I move on to a new paragraph with a logical transitions.
• This statement covers a lot of ground in a pretty short space. I discuss my family history, my goals, my educational background, and my professional background. But because the paragraphs are organized and I use specific examples, it doesn’t feel too vague or scattered.
• In addition to including information about my personal motivations, like my family, I also include some analysis about tailoring health interventions with my example of the Zande. This is a good way to show off what kinds of insights I might bring to the program based on my academic background.

Grad School Personal Statement Example: Deep Dive

Now let’s do a deep dive, paragraph-by-paragraph, on one of these sample graduate school personal statements. We’ll use my personal statement that I used when I applied to Columbia’s public health program.

Paragraph One: For twenty-three years, my grandmother (a Veterinarian and an Epidemiologist) ran the Communicable Disease Department of a mid-sized urban public health department. The stories of Grandma Betty doggedly tracking down the named sexual partners of the infected are part of our family lore. Grandma Betty would persuade people to be tested for sexually transmitted diseases, encourage safer sexual practices, document the spread of infection and strive to contain and prevent it. Indeed, due to the large gay population in the city where she worked, Grandma Betty was at the forefront of the AIDS crises, and her analysis contributed greatly towards understanding how the disease was contracted and spread. My grandmother has always been a huge inspiration to me, and the reason why a career in public health was always on my radar.

This is an attention-grabbing opening anecdote that avoids most of the usual cliches about childhood dreams and proclivities. This story also subtly shows that I have a sense of public health history, given the significance of the AIDs crisis for public health as a field.

It’s good that I connect this family history to my own interests. However, if I were to revise this paragraph again, I might cut down on some of the detail because when it comes down to it, this story isn’t really about me. It’s important that even (sparingly used) anecdotes about other people ultimately reveal something about you in a personal statement.

Paragraph Two: Recent years have cemented that interest. In January 2012, my parents adopted my little brother Fred from China. Doctors in America subsequently diagnosed Fred with Duchenne Muscular Dystrophy (DMD). My parents were told that if Fred’s condition had been discovered in China, the (very poor) orphanage in which he spent the first 8+ years of his life would have recognized his DMD as a death sentence and denied him sustenance to hasten his demise.

Here’s another compelling anecdote to help explain my interest in public health. This is an appropriately personal detail for a personal statement—it’s a serious thing about my immediate family, but it doesn’t disclose anything that the admissions committee might find concerning or inappropriate.

If I were to take another pass through this paragraph, the main thing I would change is the last phrase. “Denied him sustenance to hasten his demise” is a little flowery. “Denied him food to hasten his death” is actually more powerful because it’s clearer and more direct.

Paragraph Three: It is not right that some people have access to the best doctors and treatment while others have no medical care. I want to pursue an MPH in Sociomedical Sciences at Columbia because studying social factors in health, with a particular focus on socio-health inequities, will prepare me to address these inequities. The interdisciplinary approach of the program appeals to me greatly as I believe interdisciplinary approaches are the most effective way to develop meaningful solutions to complex problems.

In this paragraph I make a neat and clear transition from discussing what sparked my interest in public health and health equity to what I am interested in about Columbia specifically: the interdisciplinary focus of the program, and how that focus will prepare me to solve complex health problems. This paragraph also serves as a good pivot point to start discussing my academic and professional background.

Paragraph Four: My undergraduate education has prepared me well for my chosen career. Understanding the underlying structure of a group’s culture is essential to successfully communicating with the group. In studying folklore and mythology, I’ve learned how to parse the unspoken structures of folk groups, and how those structures can be used to build bridges of understanding. For example, in a culture where most illnesses are believed to be caused by witchcraft, as is the case for the Zande people of central Africa, any successful health intervention or education program would of necessity take into account their very real belief in witchcraft.

In this paragraph, I link my undergraduate education and the skills I learned there to public health. The (very brief) analysis of tailoring health interventions to the Zande is a good way to show insight and show off the competencies I would bring to the program.

Paragraph Five: I now work in the healthcare industry for one of the largest providers of health benefits in the world. In addition to reigniting my passion for data and quantitative analytics, working for this company has immersed me in the business side of healthcare, a critical component of public health.

This brief paragraph highlights my relevant work experience in the healthcare industry. It also allows me to mention my work with data and quantitative analytics, which isn’t necessarily obvious from my academic background, which was primarily based in the social sciences.

Paragraph Six: I intend to pursue a PhD in order to become an expert in how social factors affect health, particularly as related to gender and sexuality. I intend to pursue a certificate in Sexuality, Sexual Health, and Reproduction. Working together with other experts to create effective interventions across cultures and societies, I want to help transform health landscapes both in America and abroad.

This final paragraph is about my future plans and intentions. Unfortunately, it’s a little disjointed, primarily because I discuss goals of pursuing a PhD before I talk about what certificate I want to pursue within the MPH program! Switching those two sentences and discussing my certificate goals within the MPH and then mentioning my PhD plans would make a lot more sense.

I also start two sentences in a row with “I intend,” which is repetitive.

The final sentence is a little bit generic; I might tailor it to specifically discuss a gender and sexual health issue, since that is the primary area of interest I’ve identified.

This was a successful personal statement; I got into (and attended!) the program. It has strong examples, clear organization, and outlines what interests me about the program (its interdisciplinary focus) and what competencies I would bring (a background in cultural analysis and experience with the business side of healthcare). However, a few slight tweaks would elevate this statement to the next level.

Graduate School Personal Statement Examples You Can Find Online

So you need more samples for your personal statement for graduate school? Examples are everywhere on the internet, but they aren’t all of equal quality.

Most of examples are posted as part of writing guides published online by educational institutions. We’ve rounded up some of the best ones here if you are looking for more personal statement examples for graduate school.

Penn State Personal Statement Examples for Graduate School

This selection of ten short personal statements for graduate school and fellowship programs offers an interesting mix of approaches. Some focus more on personal adversity while others focus more closely on professional work within the field.

The writing in some of these statements is a little dry, and most deploy at least a few cliches. However, these are generally strong, serviceable statements that communicate clearly why the student is interested in the field, their skills and competencies, and what about the specific program appeals to them.

Cal State Sample Graduate School Personal Statements

These are good examples of personal statements for graduate school where students deploy lots of very vivid imagery and illustrative anecdotes of life experiences. There are also helpful comments about what works in each of these essays.

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However, all of these statements are definitely pushing the boundaries of acceptable length, as all are above 1000 and one is almost 1500 words! Many programs limit you to 500 words; if you don’t have a limit, you should try to keep it to two single-spaced pages at most (which is about 1000 words).

University of Chicago Personal Statement for Graduate School Examples

These examples of successful essays to the University of Chicago law school cover a wide range of life experiences and topics. The writing in all is very vivid, and all communicate clear messages about the students’ strengths and competencies.

Note, however, that these are all essays that specifically worked for University of Chicago law school. That does not mean that they would work everywhere. In fact, one major thing to note is that many of these responses, while well-written and vivid, barely address the students’ interest in law school at all! This is something that might not work well for most graduate programs.

Wheaton College Personal Statement for Graduate School Sample 10

This successful essay for law school from a Wheaton College undergraduate does a great job tracking the student’s interest in the law in a compelling and personal way. Wheaton offers other graduate school personal statement examples, but this one offers the most persuasive case for the students’ competencies. The student accomplishes this by using clear, well-elaborated examples, showing strong and vivid writing, and highlighting positive qualities like an interest in justice and empathy without seeming grandiose or out of touch.

Wheaton College Personal Statement for Graduate School Sample 1

Based on the background information provided at the bottom of the essay, this essay was apparently successful for this applicant. However, I’ve actually included this essay because it demonstrates an extremely risky approach. While this personal statement is strikingly written and the story is very memorable, it could definitely communicate the wrong message to some admissions committees. The student’s decision not to report the drill sergeant may read incredibly poorly to some admissions committees. They may wonder if the student’s failure to report the sergeant’s violence will ultimately expose more soldiers-in-training to the same kinds of abuses. This incident perhaps reads especially poorly in light of the fact that the military has such a notable problem with violence against women being covered up and otherwise mishandled

It’s actually hard to get a complete picture of the student’s true motivations from this essay, and what we have might raise real questions about the student’s character to some admissions committees. This student took a risk and it paid off, but it could have just as easily backfired spectacularly.

Key Takeaways: Graduate School Personal Statement Examples

In this guide, we discussed why you need a personal statement and how it differs from a statement of purpose. (It’s more personal!)

We also discussed what you’ll find in a strong sample personal statement for graduate school:

• A clear narrative about the applicant and why they are qualified for graduate study.
• Specific examples to support that narrative.
• Compelling reasons why the applicant and the program are a good fit for each other.
• Strong writing, including clear organization and error-free, cliche-free language.
• Appropriate boundaries—sharing without over-sharing.

Then, we provided three strong graduate school personal statement examples for different fields, along with analysis. We did a deep-dive on the third statement.

Finally, we provided a list of other sample grad school personal statements online.

What’s Next?

Want more advice on writing a personal statement ? See our guide.

Writing a graduate school statement of purpose? See our statement of purpose samples  and a nine-step process for writing the best statement of purpose possible .

If you’re writing a graduate school CV or resume, see our how-to guide to writing a CV , a how-to guide to writing a resume , our list of sample resumes and CVs , resume and CV templates , and a special guide for writing resume objectives .

Need stellar graduate school recommendation letters ? See our guide.

See our 29 tips for successfully applying to graduate school .

Ready to improve your GRE score by 7 points?

Author: Ellen McCammon

Ellen is a public health graduate student and education expert. She has extensive experience mentoring students of all ages to reach their goals and in-depth knowledge on a variety of health topics. View all posts by Ellen McCammon

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PhD in Computing & Data Sciences

For more information and to get in touch, please visit the Faculty of Computing & Data Sciences website .

The PhD program in Computing & Data Sciences (CDS) at Boston University prepares its graduates to make significant contributions to the art, science, and engineering of computational and data-driven processes that are woven into all aspects of society, economy, and public discourse, leading to solution of problems and synthesis of knowledge related to the methodical, generalizable, and scalable extraction of insights from data as well as the design of new information systems and products that enable actionable use of those insights to advance scholarly as well as practical pursuits in a wide range of application domains.

Applicants to the PhD program in CDS are expected to have earned a bachelor’s or master’s degree in one of the methodological or applied disciplines relating to the computational and data-driven areas of scholarship in CDS. They are expected to possess basic mathematical and computational competencies, and demonstrable propensity for cross-disciplinary work. To accommodate a diversity of student backgrounds and preparations, a holistic admission review is utilized. As such, GRE tests and scores are not required, but could be optionally provided and considered as part of the applicant’s portfolio, which may also include evidence of prior, relevant preparation, including creative works, software code repositories, etc. Special attention will be paid to applicants from underrepresented minorities in computing and data science disciplines.

Completion of the PhD degree in CDS requires coursework covering breadth and depth topics spanning the foundational, applied, and sociotechnical dimensions of computing and data science; completion of research rotations that expose students to ongoing projects; completion of a cohort-based training on ethical and responsible computing; and successful proposal and defense of a doctoral thesis.

For their thesis work, and in preparation for careers in academia, industry, and government, CDS PhD students are expected to pursue theoretical, applied, or empirical studies leading to solution of new problems and synthesis of new knowledge in a topic area determined in consultation with their mentors and collaborators, which may include external researchers and practitioners in industrial and academic research laboratories.

Upon completion of the program, students will be prepared to pursue careers in which they lead independent cutting-edge research and development agendas, whether in academia (by teaching, mentoring, and supervising teams of students engaged in scholarly pursuits) or in industry (by collaborating, directing, and effectively managing diverse teams of practitioners working at the forefront of industrial R&D).

Learning Outcomes

The following learning outcomes explain what you will be able to do at the end of your time as a CDS PhD candidate, as a result of earning your degree.

• Exhibit a strong grasp of the principles governing the design and implementation of the methodological approaches for computational and data-driven inquiry.
• Identify the literature and demonstrate mastery of the compendium of works relevant to a well-defined area of research inquiry in computing and data sciences.
• Show capacity to engage meaningfully in and materially contribute to multidisciplinary research and development endeavors.
• Evidence a strong sense of social and professional responsibility for decisions related to the development and deployment of computational and data-driven technologies.
• Assess and argue the merits, limitations, and possibilities of new research work in a specialized area at the level commensurate with standards of scholarly venues in that area.
• Formulate and pursue a research agenda leading to solution of new problems and to synthesis of new knowledge shared through peer-reviewed publications.

Course Requirements

Sixteen semester courses (64 credits) are required for post-BA/BS students and 12 semester courses (48 credits) are required for post-MA/MS students. Students with prior graduate work (including master’s degrees) may be able to transfer up to two courses (8 credits) as long as these credits were not used to fulfill matriculation requirements, upon the recommendation of the student’s academic advisor, and subject to approval by the Associate Provost for CDS.

Of the 16 courses, up to 3 undergraduate courses (12 credits) may be counted as background courses, selected in consultation with the student’s academic advisor and subject to approval by the Associate Provost for CDS. Other than these remedial courses, all other courses must be graduate-level courses or directed studies offered by CDS or by other BU departments in order to satisfy the following degree requirements.

The methodology core requirement ensures that students possess foundational knowledge and competencies in a subset of the following eight methodological areas of CDS:

• Mathematical Foundations of Data Science
• Statistical Modeling and Inference
• Efficient and Scalable Algorithms
• Predictive Analytics and Machine Learning
• Combinatorial Optimization and Algorithms
• Computational Complexity
• Programming and Software Design
• Large-scale Data Management

A list of courses that can be used to satisfy these competencies will be maintained on the website for CDS. Students who start their PhD program in CDS are expected to satisfy at least six of these competencies. Students who complete the course requirement for the PhD program in a cognate discipline are expected to satisfy at least four of these competencies.

The subject core requirement ensures that students establish depth in one area of inquiry that is aligned with either the methodological or applied dimensions of CDS. Subject areas are defined by groups of CDS faculty members working in related disciplinary and/or interdisciplinary areas of research who expect their prospective students to have enough depth in the subset of topics to enable them to tackle doctoral-level research in these topics. The set of subject areas as well as a list of preapproved graduate-level courses offered in CDS or elsewhere at BU that can be used to satisfy each subject area will be maintained on the website for CDS.

During the first two years in the program, all PhD candidates in CDS must complete three cohort-based requirements; namely, a two-semester training course (4 credits) covering various aspects of the responsible and ethical conduct of computational and data-driven research, a two-semester doctoral seminar (4 credits) that introduces them to the research portfolios of CDS faculty members as well as to the skills and capacities needed for success as scholars, and at least two research or lab rotations (8 credits) that expose them to real-world computational and data-driven applications that must be tackled through effective multidisciplinary teamwork.

A cumulative GPA not less than 3.3 must be maintained for all non-Pass/Fail courses taken to satisfy the methodology core requirement and the subject core requirement of the degree, excluding any background courses and excluding any transferred credits. Students who receive grades of B– or lower in any three courses taken at BU will be withdrawn from the program.

Language Requirement

There is no foreign language requirement for the PhD degree in CDS.

Qualifying Examinations

No later than the end of the sixth semester (third year), all PhD candidates in CDS must pass a public oral examination administered by a committee of three faculty members, chaired by the student’s research (and presumptive thesis) advisor or coadvisors. The oral area exam is meant to establish the student mastery of a well-defined area of scholarship and preparedness to pursue original research in that area. The oral area examination may require completion of a survey paper or completion of a pilot project ahead of the examination. The scope as well as any additional requirements needed for the examination should be developed in consultation with and approval of the research advisor(s), at least one semester prior to the exam.

Dissertation and Final Oral Examination

Candidates shall demonstrate their abilities for independent study in a dissertation representing original research or creative scholarship. A prospectus for the dissertation must be successfully defended no later than the end of the eighth semester (fourth year) of study.

Candidates must undergo a final oral examination no later than the end of the 10th semester (fifth year) of study in which they defend their dissertation as a valuable contribution to knowledge in their field and demonstrate a mastery of their field of specialization in relation to their dissertation.

Both the prospectus and final dissertation must be administered by a dissertation committee of at least three readers (including the dissertation advisor or coadvisors) and chaired by a CDS faculty member who is not one of the readers.

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• PhD in Computing & Data Sciences
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Data Science MSc personal statement

• Reading time: 3 minutes
• Price: Free download
• Published: 13th September 2019
• Word count: 616 words
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Like the vast and ever-expanding universe, the big data fields are in a perpetual expansion mode. Both fascinate me. The sheer volume and complexity of data being generated in today’s world present unprecedented opportunities for exploration and analysis. Harnessing the power of data can lead to groundbreaking discoveries, transformative insights, and innovative solutions to some of the most pressing challenges we face.

My education has provided me with a strong foundation to navigate this data-driven landscape. Through my coursework in computer science, I have gained a deep understanding of algorithms, data structures, and programming languages, all of which are crucial components in extracting meaningful information from large datasets. This knowledge has not only enabled me to work comfortably with computers and numbers but has also fostered my passion for leveraging data to uncover valuable insights.

Building on my educational foundation, my work experience in the field of technology and business management has allowed me to put theory into practice. I have had the opportunity to work on large-scale, data-intensive projects that have exposed me to the challenges faced by various industries and governments. The experience has strengthened my ability to analyze complex datasets, identify patterns, and derive actionable intelligence that can drive informed decision-making.

In this era of big data, organizations have come to realize the importance of transitioning from traditional methods to data-driven approaches. It is now essential to understand and process all aspects of data and analyze it effectively to arrive at optimal choices for decision-making. This realization has sparked a surge in demand for professionals who possess the skills and expertise to transform raw data into meaningful insights. I have been fortunate enough to develop hands-on experience with programming languages like SQL and JSON, as well as data visualization tools like Excel and Tableau. These practical experiences have allowed me to deepen my understanding of data analysis techniques and strengthen my ability to communicate complex information visually.

Furthermore, my passion for big data extends beyond technical proficiency. I am captivated by the immense potential of predictive analytics and artificial intelligence (AI). The ability to leverage advanced algorithms and machine learning models to uncover hidden patterns, forecast trends, and make data-driven predictions holds tremendous promise for addressing complex challenges across industries. By exploring these fields, I aim to contribute to the development and application of AI techniques that can empower organizations and individuals to make informed decisions and drive positive change.

As I look ahead, my goal is to be a Data Scientist and contribute to an organization’s data-driven decision-making processes. I am particularly excited about the prospect of applying my skills and knowledge to real-world scenarios, where I can utilize data to uncover insights and create innovative solutions. Ultimately, I envision establishing my own enterprise that focuses on mentoring and guiding the next generation of data scientists, fostering a community of individuals dedicated to using data for social good and addressing pressing challenges.

The MSc Data Science program with an industry placement at Essex University aligns perfectly with my aspirations. Its comprehensive curriculum and emphasis on practical application will provide me with the theoretical foundation and hands-on experience necessary to excel in the field. I am eager to immerse myself in an environment that fosters collaboration, innovation, and critical thinking, where I can learn from esteemed faculty and engage with like-minded peers.

In conclusion, my passion for big data, combined with my educational background and industry experience, fuels my desire to pursue the MSc Data Science program at Essex University. By expanding my knowledge, developing advanced analytical skills, and immersing myself in real-world applications, I am confident that I will be well-prepared to make a meaningful impact in the world of data science .

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What Is a PhD Personal Statement?

How to structure your personal statement, final thoughts, phd personal statements.

Updated March 14, 2023

When applying for a PhD position, a personal statement is often required. This can be the case whether you are applying for an advertised PhD research project or with a personally devised project.

This personal statement is separate from your PhD research proposal, which will go into much greater detail about the PhD project you are proposing or applying to undertake.

This article will delve into what to your PhD personal statement should contain and how to structure it for the best chance of success.

A PhD personal statement will support your application and is intended to shed more light on your motivations, academic background/ achievements and personal strengths .

Your statement will most likely be read by the admissions tutor for the department, who, based on your statement and research proposal, will decide whether your application should progress to the next stage of the process.

A personal statement will not always be required, so make sure to check the requirements for your institution and department.

What Should a PhD Personal Statement Contain?

When writing your PhD personal statement, you will need to convey your suitability for the programme or position, indicating that you have the academic ability, background knowledge and drive to take on a project of this level of complexity.

Statements are expected to be heavily related to the discipline and research angle being proposed. Your statement should draw out the strands of your previous exploration and research and illustrate what led you to apply to complete this particular PhD project.

It should discuss your interest in the subject matter, your academic interests within the field and your motivations for applying to the institution in question.

Below is a list of topics that need to be addressed in your personal statement .

The examples provided are for illustrative purposes only. It is important that your writing is grounded in your own experiences and aspirations, and consistently linked to your research proposal.

1. Why You Want to Do This PhD

It is important to talk about your motivations for undertaking the project, along with an awareness of the challenges you may experience, as this will display your drive for completing your research.

Directly reference your research proposal, talking about how your current or previous studies relate and have prepared you to undertake this project.

The strongest argument for why you want to undertake the PhD will come from the arc of your academic research and displaying a genuine enthusiasm for advancing the research of your chosen field.

During my master’s degree at the University of Nottingham, I had two primary focuses: cultural behaviours and social media impacts. I was interested in how culture reacts under new stimuli, so I wrote my dissertation on how cultural practices can be newly read through the lens of media platforms. My proposed research proposal takes this theoretical and desk-based research a step further, exploring the reflections of the specific cultural practice of...

2. How Your Work Will Benefit the University

When applying for a PhD, what you will bring to the university as a junior academic is an important factor in the decision-making process. You will not just be a student but a member of the department, most likely with teaching responsibilities.

The faculty will want to know that you can meaningfully contribute to the department through both your research and teaching.

If your work links into other PhD projects currently being supervised, or to the research of a senior academic or professor, it is good to indicate these connections and the potential they hold – whether this is in terms of supportive research, a complementary strand or a new angle or perspective.

If there is an academic whose work you are particularly interested in and you have not already indicated that you would like the opportunity to work alongside them, highlight this. Display that you are knowledgeable about the department’s current research interests, specialities and standing.

Since beginning my MSc research and developing a more specific interest in mangrove restoration, I have closely followed the research being conducted by Professor Stephens into restoration and wave attenuation. As I subsequently elaborate upon in my research proposal, I believe that my project fruitfully intersects with this research. It aims to make a meaningful contribution to a department world-renowned for its research into marine and coastal climate change impacts.

3. Why You Want to Study for a PhD at This University

It is important to convey why you want to conduct your research specifically at the institution you are applying to. Admissions will want to know that you have thought carefully about your application and know exactly what undertaking a PhD with their department will involve.

Conveying this intersects with the sentiments of the above point, as you should display that you have investigated the work of the professors in the department and are aware of any individual research groups or projects that relate to your work. These intersections help to show why the university is the best choice for you.

I believe that the University of Cardiff offers the best reciprocal environment in which to grow and diversify my approach to this research. Working alongside my supervisor, I intend to tap into the departmental expertise on biodiversity mapping and – using the framework of the 2019 report by Fischer, Raymond and Wills – reveal new insights by building upon the current research.

4. Why You Are the Best Candidate

The PhD personal statement is an opportunity to promote yourself, so it needs to be specific, personal and unique – nobody else has your history, aspirations or skill set, so explain what it is about you that makes you best suited to this endeavour.

When stating that you possess certain skills, back them up with concrete examples or explanations that are unique to you.

Be wary of making your personal statement too general or simply writing what you believe the admissions team want to hear. There are no correct answers, perfect CVs or ideal academic paths to have followed to reach this point. Your personal statement should reflect your journey and what you have gained from it, segues and unconventional routes included.

During my English Literature master’s degree, I focused on videogames and late medieval literature. I could see at that point that literary studies had a lot to offer the study of games and that games provided interesting new angles for applying longstanding theoretical approaches and fields. This led me to complete a further master’s degree in videogames as I sought to apply my research in a more specific and digitally focused arena. I found, because of my background in humanities and literary theory, that I possessed a perspective that my fellow empirically-minded colleagues, with backgrounds in coding, lacked. Using this unique perspective, I am now seeking to develop the research of my master’s dissertation through a PhD project

5. What You Learned During Your past Degrees and the Skills You Developed

To get to this stage, you will have already spent many years devoted to studying and growing your interest in your subject matter, so sell yourself and your talents. Think about the individual and group projects you have undertaken and the skills they helped you to develop and hone.

Remember to be specific and relate your skill set back to your proposed PhD project. For example, talk about the methodological approaches you have used previously to yield results, the new connections and collaboration you fostered across disciplines, or the positive impact made by projects you were involved in.

Your examples will vary greatly depending upon your academic background and the PhD you wish to complete but, regardless of topic, it is important to reveal your high level of skill and competence.

During my MSc, I conducted fieldwork in [location] and gained direct experience of collecting samples for paleolimnological analysis. I developed an aptitude for rapid algal species analysis and enjoyed the challenge of comparing this population data across cores and sample locations. This practical background has enabled me to be confident in my ability to source and analyse the sediment cores I require for this PhD project.

6. Any Explanations for Lower Grades (If Applicable)

If you have any extenuating circumstances for any results or grades, do not be afraid to explain the situation in your statement. Be honest about your struggles or challenges and seek to convey how you have grown as a consequence of these.

7. Your Future Plans

It is important to have thought carefully about your plans for life after your doctorate, as displaying clear goals will help the admissions team to determine that you have the correct motivations for applying.

Having a considered path you intend to follow beyond your proposed research gives confidence in your dedication to the project. Someone with articulated ambitions is more likely to be committed to the programme in the face of challenges.

If you wish to pursue a career in academia, as many PhD graduates do, show that you are aware of what this will involve. If you have a different industry path in mind, don’t be afraid to share it in your statement. PhDs can lead on to a variety of different career paths, so impress the admissions team with your aspirations of practical application.

The university will also want to ensure they can provide you with the skills and training you require to be successful and reach your goals. Letting the department know early on about your aspirations can help to ensure that the tailored support you will require can be provided.

After completing my PhD here, I intend to pursue an academic career within an architectural faculty in the UK. If the opportunity is available, I will be looking to apply for a lecturing position within this department. I am, however, acutely aware of the fierce competition in this field. I will be proactively seeking legacy funding for my research project as its potential to inform the typologies of housing used for settlement upgrading extends well beyond the timescale of this PhD.

If you are applying to more than one institution, which is highly likely, ensure that you tailor your personal statement to each university. Taking the time to craft a statement that speaks to the specificities of the university and the research of the teaching department will exponentially increase your chances of moving on to the next stage in the admissions process.

Below are our tips for structuring your PhD statement. You must ensure that you are aware of all the requirements set out by the university to which you are making your application, as these will influence the structure and content of the piece.

Step 1 . Structure

PhD applicants are expected to be highly adept at writing, so it is paramount that your personal statement is carefully constructed and reflects your ability for written communication .

The university you are applying to may provide you with a word count , or it may be stipulated by the space allowed on an online application form . Check if this is the case, as it is far easier to write to a specific word limit rather than having to make extreme edits to a piece that exceeds accepted length.

A PhD personal statement should be approximately one to one-and-a-half pages in length and be split into clear and concise paragraphs. If a sentence does not add value to the personal statement, omit it.

As a guide, aim for between four and six paragraphs , depending on their length. As previously indicated, it is best to keep paragraphs shorter rather than longer, as this will make your statement easier and more enjoyable for the admissions team to read.

Open your personal statement with a context-setting introduction regarding your academic interests and what has led you to apply for this research project. Seek to convey a real sense of yourself, so that those who read your statement can get a genuine sense of the student and junior academic you will be.

In the middle paragraphs , explore your motivations in greater detail, along with the qualities that make you a suitable candidate– with examples of when you displayed them.

It is important to provide a closing paragraph , bringing together the strands in your statement to solidly iterate why you are the right candidate.

Although it is best to avoid clichés and keep your writing original and interesting, conclude your personal statement by thanking the admissions tutor for taking the time to read your statement and considering your application.

Step 2 . Tone

When writing your statement, use a formal tone , correct grammar and appropriate language.

Colloquial and familiar language should be avoided. It is important to talk about your past academic and, perhaps, fieldwork or research experiences, but keep these professional in tone rather than anecdotal.

Ask someone to read through your statement to sense-check the tone and language used. It is always good to get a new perspective, particularly on a piece you spent a long time crafting.

Ensure you thoroughly check your grammar and spelling using the spell check function on your computer and also by eye. If including complex academic terminology, double-check that your terms are spelt correctly and have not been mistyped or incorrectly recognised and changed by your computer.

Writing a personal statement that accurately reflects your achievements, abilities and drive to take on your PhD can be a difficult task.

It is important to leave yourself enough time to write a draft statement so you can receive outside feedback, review it yourself and make the necessary improvements to ensure your piece does your potential as a PhD student justice.

Demonstrate your suitability for doctoral work with a personal statement that is personal to you and your unique experience and skills. A carefully thought-out, well-structured and well-evidenced statement will sell yourself and your academic abilities.

Seek to connect with those who read your application, explaining why your journey has equipped you for completing a PhD you will be proud of.

You might also be interested in these other Wikijob articles:

Or explore the Postgraduate / PHD sections.

For Prospective Students

Introduction to the biomedical data science graduate program.

Biomedical Data Science is an interdisciplinary field that combines ideas from computer science and quantitative disciplines (statistics, data science, decision science) to solving challenging problems in biology and medicine. Applicants enter our program with many different backgrounds, so the program is designed to be flexible. Training in informatics and biocomputation is also available through other departments at Stanford, such as Bioengineering, Computer Science, Statistics, and Genetics. We recommend your explore the various options to find the best fit for you.

Important Dates:

Application Deadlines: December 5th for PhD and Academic MS; other MS applications accepted quarterly.

Mentoring and Info sessions : Faculty Online Information Sessions will be scheduled in the summer for the fall term, 2024. Meet-the-Students Online Panel will be scheduled in the summer for the fall term, 2024. Peer-to-Peer Application Mentoring Program registration deadline will be scheduled in the summer for the fall term, 2024.

What DBDS Offers

• The Academic (Research) MS, with NLM-funded positions for postdoctoral trainees; others may also apply, but are not guaranteed funding from DBDS.
• The Honors Cooperative Program (Professional Masters) MS, a part-time distance education program
• The Coterminal MS for Stanford undergraduates
• Certificate in Bioinformatics
• Individual courses
• Post-doctoral research training (not pursuing a degree)
• Scholarly Concentration and Med Scholars programs for Stanford Medical Students

Why apply here?

Prerequisites, diversity and inclusion, phd + masters of medicine, academic (research) ms, honors cooperative program (hcp) ms, coterminal ms, writing your personal statement, postdoctoral training, clinical informatics fellowship, distance education programs, for stanford medical students, for stanford mstp students, for stanford graduate students, for stanford undergraduates, for international applicants, why apply to this program.

• Reputation . Stanford is ranked #1 for graduate training in Biological Sciences (including  Genetics/Genomics ), Bioinformatics , Computer Science , and  Statistics . You will work with world-renown leaders in these areas.
• Interdisciplinary Research . DBDS is part of the Stanford Biosciences PhD program, and draws on faculty from research and clinical departments located throughout Stanford’s School of Medicine. We have access to the extensive research clinical database and clinical informatics expertise at Stanford Hospital and Lucile Packard Children’s Hospital. In addition, we have strong ties to Bioengineering, Computer Science and Statistics. All of these are in close physical proximity on Stanford’s main campus.
• History . Founded in 1982, our program is one of the oldest and most illustrious in the United States. Our graduates have gone on to become distinguished faculty at top universities and medical schools, industry leaders at major corporations and startups, or high-ranking positions in government.
• Curriculum . Our core courses span a wide array of topics, from the analysis of biological sequences and structures, to translational and imaging informatics, the use of clinical data to drive health care, and understanding the principles of developing models and representations of biomedical phenomena. Much of the course material is based on cutting-edge research conducted here at Stanford. Electives come from DBDS, Computer Science, Statistics, and other departments.
• Scientific Communication . We place a very high value on being able to present complex ideas to colleagues, collaborators, and the public in speech and in writing. Students present annually at our research seminar. All students make presentations regularly in their labs.
• Community . DBDS is a small, collegial, friendly program. We have an annual off-campus retreat, and a strong alumni network.
• Location . Stanford University’s campus occupies over 8000 acres, bordering Palo Alto, California. It has an ideal Mediterranean climate, is the heart of Silicon Valley, and provides easy access to the amenities of the San Francisco Bay Area.

Prerequisites for Graduate Degrees in Biomedical Data Science

Our program is quite quantitatively and computationally rigorous, and our students take graduate-level coursework in statistics and computer science at Stanford. Therefore, we expect strong preparation in these areas in order to make reasonable progress through our curriculum. All of our degree programs have the same prerequisites. Note that these are the minimum requirements, and that many applicants exceed them.

• Calculus: at least one year, preferrably the track taught for engineering or physical science. Additional coursework in multivariate calculus is  strongly  recommended
• Probability and statistics: at least one course, and preferably one course in both areas
• Linear algebra
• Computer science: one year, preferably the introductory sequence for CS majors. The focus should be fundamentals of computer science (data structures and algorithms) and software engineering principles (abstraction, modularity, object-oriented programming)
• Biology/Medicine: at least some coursework in this area, preferably the introductory sequence for biology majors

The Department of Biomedical Data Science recognizes that the Supreme Court issued a ruling in June 2023 about the consideration of certain types of demographic information as part of an admission review. All applications submitted during upcoming application cycles will be reviewed in conformance with that decision.  

The Department of Biomedical Data Science welcomes graduate applications from individuals with a broad range of life experiences, perspectives, and backgrounds who would contribute to our community of scholars. The review process is holistic and individualized, considering each applicant’s academic record and accomplishments, letters of recommendation, prior research experience, and admissions essays to understand how an applicant’s life experiences have shaped their past and potential contributions to their field and how they might enrich the learning community at Stanford.

We would like to make applicants aware of the following Stanford programs and resources:

DBDS Peer-to-Peer Application Mentoring Program

The DBDS Peer-to-Peer Application Mentoring Program is a student organized initiative that strives to assist individuals who:

• Identify as part of one or more groups that are historically underrepresented in STEM and
• Are applying to the DBDS PhD or MS program.

Participants may receive one round of feedback on their statements of purpose, up to the limit of our time and resources. Participation does not guarantee nor increase chance of admission.

The Peer-to-Peer application will be available in the fall term, 2024.

Meet the Students Panel

The Biomedical Informatics graduate students panel will be scheduled in the fall term, 2024.

Meet the Faculty Panel

Join our Meet the Faculty Panel will be held in the fall term, 2024.

Other Programs:

• SSRP-Amgen Scholars Program , an eight-week, residential, summer research program for current undergraduates, with a goal of bringing diversity to graduate study in the biomedical sciences, including Biomedical Data Science.
• Stanford’s Biosciences  ADVANCE Summer Institute  to prepare students for a successful graduate career.
• Stanford’s Biosciences Graduate Program  Diversity & Engagement  website.
• Stanford’s Vice Provost for Graduate Education  Diversity in Graduate Education  website.
• Stanford’s  Office of Accessible Education
• Stanford’s  SCRIBE  system to convert documents to Braille and audio formats.

We have admitted students who have previously studied at the following institutions across the world:

All India Institute Medical Sc Amherst College Andhra University Arizona State University Ateneo De Manila University Bar-Ilan University Baylor University Beijing Inst Chem Fiber Engine Bharathidasan University Birla Institute of Tech and Sc Boston College Boston University Brandeis University Brigham Young University Brown University Calif Polytechnic State Univ Carnegie Mellon University Case Western Reserve Univ Central University of the East City College of New York Claremont Graduate School Claremont McKenna College Clark College Clark University Colby College Columbia University Cornell University CUNY Mount Sinai School Me Dartmouth College Davidson College De Anza College Drexel University Duke University Ecole Polytechnique Emory University Florida State University Fudan University George Mason University George Washington University Georgetown University Georgia Institute of Tech Harvard University Harvey Mudd College Hendrix College Hitotsubashi University Howard University HS Affiliated Renmin Univ Indian Institute of Technology Indiana University Indiana-Purdue University Indi Iowa State University Iran Univ Science & Technology Johns Hopkins University Leeward Community College Lomonosov Moscow State Univ Louisiana State Univ Medical C Loyola University of Chicago Ludwig Maximilian Universitat Marlborough College Massachusetts Inst of Tech McGill University Mesa Community College Monash University Morehouse College Mumbai University National Chiao Tung University National Taiwan University National University Singapore New College of Florida New York Medical College New York University North Harris County College Northwestern University Parkland College Peking Union Medical College Pennsylvania State University Pomona College Portland State University Princeton University Queens University at Kingston Rush University Rutgers University S.U.N.Y. State Univ at Bingham S.U.N.Y. State Univ at Buffalo Saddleback College Saint Andrew’s College Saint Andrew’s Junior College San Diego Miramar College San Diego State University San Francisco State University San Jose City College Santa Clara University Seoul National University Shanghai Jiaotong University Smith College Solano Community College Southwestern College St John’s College St Marys College Stanford University Swarthmore College Syracuse University Technion Israel Inst of Tech Temple University Tsinghua University Tufts University Tulane University of Louisiana Univ of California Berkeley Univ of California Davis Univ of California Irvine Univ of California Los Angeles Univ of California San Diego Univ of California San Francis Univ of Illinois Urbana-Champa Univ of Michigan Ann Arbor Univ of Southern California Universidad De Los Andes Universidad Del Valle Universidad Nacional Autonoma Universidad Nacional De Rosari University of Akron University of Alabama Tuscaloo University of Alberta University of Baghdad University of Calgary University of Cambridge University of Canterbury University of Chicago University of Cincinnati University of Edinburgh University of Florida University of Georgia University of Guelph University of Hawaii Manoa University of Maryland Balt University of Maryland College University of Massachusetts Bo University of Melbourne University of Miami University of Minnesota Twin C University of Missouri Kansas University of New Mexico University of New South Wales University of Notre Dame University of Oxford University of Pennsylvania University of Phoenix University of Pittsburgh University of Pune University of Rajasthan University of Sydney University of Texas Austin University of Tokyo University of Toronto University of Utah University of Virginia University of Waterloo University of Western Ontario University of Wisconsin Madiso Vellore Institute Technology Virginia Commonwealth Universi Washington State University Washington University Weizmann Institute of Science Wesleyan University Worcester Polytechnic Institute Yale University

The PhD Degree in Biomedical Data Science

The PhD degree allows graduates to lead research in academic, industry, or government positions. All prospective applicants should note that the program in Biomedical Data Science is intellectually rigorous, and emphasizes research in novel computational methods aimed at advancing biology and medicine. You may also want to investigate degree programs from other computational and quantitative graduate programs (Bioengineering, Computer Science, Statistics) and other programs in the Biosciences Programs (such as Genetics, Chemical & Systems Biology, or Structural Biology). In contrast to the other computational/quantitative programs, DBDS focuses more on informatics issues of knowledge representation and reasoning, data mining and analysis, and machine learning, while in contrast to the Biosciences programs, DBDS places greater emphasis on method development and evaluation than on basic science. Faculty from many departments have research projects of a computational nature, and in some cases there is considerable overlap, but our applications committee evaluates the fit of your application to our program, so the choice of a home program is an important one.

Our students come from diverse backgrounds and training experiences. Some enter straight from baccalaureate training, while others have pursued advanced degrees, such as an MS, MPH, or MD, or worked in clinical medicine, bioengineering, biotechnology, or software engineering.

Please see the  prerequisites  page.

Degree Requirements

The curriculum is described on  Stanford ExploreDegrees .

The doctoral program is a full-time, residential, research-oriented program. DBDS does not offer part-time or distance education leading to the PhD. However, some students have applied to the part-time distance education MS program, completed that degree, and then submitted a separate application to the PhD program. There is no guarantee that Masters graduates will be accepted into the PhD program.

PhD students typically start in the fall quarter, but may begin in the preceding summer. They spend an average of about five years at Stanford.

Candidates are encouraged to explore the various research interests of the biomedical informatics core and participating faculty. Lab rotations during the first year expose students to different labs and faculty. Prior to being formally admitted to candidacy for the doctoral degree at the end of the second year of study, each student must demonstrate knowledge of informatics fundamentals and a potential for succeeding in research by passing a qualifying examination. Students later complete and defend a doctoral dissertation.

MDs interested in the PhD should contact us early, especially if you are coordinating the DBDS training with further medical residency or fellowship training. It is also important to ensure that sufficient math and computer science prerequisites are completed before applying.

BMI follows the same funding model as other programs in Biosciences: all of our PhD students are fully funded, and, at time of starting graduate school, your funding does not tie you to any particular lab, giving you the freedom to explore your research interests at Stanford. All funding sources cover tuition, a stipend, and health insurance. However, there are some restrictions:

US Citizens and permanent residents are eligible for our National Library of Medicine (NLM) Training Grant. They can also apply for National Science Foundation Graduate Fellowships, and other external fellowships; this is encouraged, but not required.

Join dozens of  Stanford Medicine students  who gain valuable leadership skills in a multidisciplinary, multicultural community as  Knight-Hennessy Scholars  (KHS). KHS admits up to 100 select applicants each year from across Stanford’s seven graduate schools, and delivers engaging experiences that prepare them to be visionary, courageous, and collaborative leaders ready to address complex global challenges. As a scholar, you join a distinguished cohort, participate in up to three years of leadership programming, and receive full funding for up to three years of your PhD studies at Stanford. Candidates of any country may apply. KHS applicants must have earned their first undergraduate degree within the last seven years, and must apply to both a Stanford graduate program and to KHS. Stanford PhD students may also apply to KHS during their first year of PhD enrollment. If you aspire to be a leader in your field, we invite you to apply. The KHS application deadline is October 11, 2023. Learn more about  KHS admission .

NSF Graduate Research Fellowship Program (GRFP) . Open to first  or  second year graduate students. Eligibility: No previous graduate training (e.g., masters degree), must be US citizen or permanent resident. Due date: late October.

We do not accept “self-pay” PhD students.

Application Instructions and Deadlines

Applications are due late November/early December each year. See details on the  Graduate Admissions webpage  and on the  Biosciences Application  website.

The Application Deadline: December 5, 2023 (11:59:59 pm PST).  

• Note that the Biosciences Program allows you to select two departments/programs from which you will receive simultaneous consideration. Also note that only one PhD application per academic year is allowed, and that Computer Science, Bioengineering, and Statistics are not part of the Biosciences Program.
• Submit scanned (unofficial) transcripts as part of the Biosciences application.  Graduate Admissions  only requires admitted applicants who accept the offer of admission to submit official transcripts that shows their degree conferral. Please do not send or have sent any official transcripts to us at this time.
• See our page about the  Personal Statement .
• Please include an up-to-date version of your CV.

The GRE General Test score is not required and will not be considered if submitted. We do not require any GRE Subject Test scores.

• Letters of recommendation cannot be mailed, emailed, faxed, or submitted through a letter service (with the exception of Interfolio). For letters submitted via Interfolio, please remember that letters written specifically for your Stanford graduate program tend to be stronger than letters written for general use purposes.
• For materials that are mailed, please use our  Contact Address .
• Please do NOT upload supporting materials, such as published papers, unpublished manuscripts, BS or MS theses, writing samples, posters, or class projects, with your application .
• To check your application status,  click here to Visit Your Status Page . Interview invitations go out in early January, and interviews are in late February or early March. Offers of admission are made on a rolling basis starting in March. Finals decisions from admitted candidates are due by April 15.
• The selection of PhD students admitted to DBDS is based on an individualized, holistic review of each application, including the applicant’s academic record, the letters of recommendation, the statement of purpose, personal qualities and characteristics, and past accomplishments.
• Deferral of admission: DBDS generally does not allow deferral of admission to the PhD program, and it is better for you to apply when you are ready to begin your graduate study following the normal timeline. However, sometimes one’s circumstances change; please contact us if that happens to you.

Frequently Asked Questions

It is highly recommended that you review our  Frequently Asked Questions  page.

The PhD with Masters of Medicine

The Masters of Medicine (MOM) is for students also pursuing the PhD. This combined degree program trains graduates who will conduct basic research with relevance to current problems in medicine. Candidates receive shared training with Stanford medical students and through seminars in translational medicine. The MOM program takes at least one additional year. Students interested in the MOM and PhD program must be accepted into the PhD program before they are eligible to apply for the MOM.

The MOM program supports students through a scholarship during their MOM training. The program does not accept candidates who do not qualify for the scholarship. The balance of the PhD training is funded through the usual DBDS mechanisms.

Application Instructions

See  Masters of Medicine  website for application instructions.

Combined MD/PhD

The MD and PhD degrees may be pursued jointly through the  Medical Scientist Training Program .

The PhD Minor in Biomedical Data Science

The PhD minor in Biomedical Data Science is designed for graduate students in allied departments to acquire specialization in biomedical informatics during their graduate studies. The PhD minor is open to Stanford graduate students only, and is not a formal degree. The minor may be of particular interest to those in Bioengineering, Computer Science, Electrical Engineering, Statistics, Biology, or any of the Bioscience Programs. Consider if the minor will advance your research career, and consult with your academic and research advisors in your home department.

Prerequisites depend on the classes you select for the minor but generally you should have completed at least most of what we have listed on our  Prerequisites page . Note that you cannot use any class numbered below 200 to contribute to the 20 units required for the minor.

Requirements

See the section on Biomedical Data Science  PhD Minor  in the Stanford Bulletin, especially the information about  not double counting course units .

The Biomedical Data Science Training Program is unable to fund the PhD minor.

You will need to submit the following three documents:

• The application form from the Registrar’s office. List the courses for your program of study that fulfill the University’s and DBDS program requirements.
• A copy of your unofficial transcript.
• A one-page statement of purpose.

You may submit your application any time during the academic year to our  Contact Address.

Academic MS in Biomedical Data Science

The Academic MS degree is a full-time, on-campus, research-oriented program, and is for candidates with an interest in academic or research positions. The MS requires 45 units taken at Stanford. Most will be taking 10 units per quarter, so this program typically lasts 1.5 to 2 years.

A research project is required for completion of the degree. Trainees are encouraged to participate in one or more research rotations during their first year.

All students are expected to participate fully in the program events including Journal Clubs, research presentations, orientations, retreats, and the National Library of Medicine’s Informatics Training Conference (if funded by NLM).

MDs interested in the Academic MS should contact us as early as possible, especially if you are coordinating the DBDS training with further medical residency or fellowship training. It is also important to ensure that sufficient math and computer science prerequisites are completed before applying. This degree program is not appropriate for those with little to no quantitative or computational skills; you might want to consider Health or Clinical Informatics masters programs elsewhere, or the Clinical Informatics Fellowship .

Clinicians who wish to maintain their clinical activities may do so, but should be aware that the NLM training grant restricts outside employment to eight hours per week. The DBDS program does not arrange appointments to clinical positions or to subspecialty fellowship training.

Our NLM funding for this degree is limited to post-doctoral scholars who are US citizens or permanent residents; others, including predoctoral or international candidates, will have to get external funding or pay themselves. In this context, postdoctoral means those holding one of these degrees: PhD, MD, DDS, DMD, DO, DVM, OD, DPM, ScD, EngD, Dr PH, DNSc, DPharm, DSW, or PsyD. Post-doctoral scholars are required under the terms of the funding to devote at least 50% time to research and 50% towards classes, and because of the terms of the NLM funding, we would prefer they remain in the program in increments of full years (typically, two). Note that there are limits on the number of years of NIH funding one may receive. The exact rule is: “No individual trainee may receive more than 5 years of aggregate Kirschstein-NRSA support at the predoctoral level and 3 years of aggregate Kirschstein-NRSA support at the postdoctoral level, including any combination of support from Kirschstein-NRSA institutional research training grants and individual fellowships.” ( National Institute of Health Grants Policy page )

Also, if you are currently pursuing a PhD degree (at Stanford, or elsewhere) you may apply for our postdoctoral MS funding. Note that we cannot appoint you to the NLM Training Grant until your PhD has been conferred, so it is important that your estimated graduation date be correct.

For applicants who are not postdoctoral, we do not guarantee funding, and you are responsible for arranging your own support. You can pursue external fellowships (although these are rarely available for MS students). If admitted, you can contact faculty in whose research you have interest, and see if they have research funds to support you. International applicants should read our  webpage .

Applications are due early December each year. Note: Applications should be submitted beginning mid-September and will not be considered before that. See details on the  Graduate Admissions webpage  and on the  Biosciences Application  website.

The Application Deadline: December 5, 2023 (11:59 pm PST)

• Application materials, including letters of recommendation, should be received by the deadline. We do review all applications, including incomplete ones.
• Please do NOT upload supporting materials, such as published or unpublished papers, posters, or class projects, with your application.
• If the application is incomplete, the Biomedical Data Science Admissions Officer will notify the applicant by February. For post-doctoral candidates, there is no special paperwork or application required to apply for NLM funding. There is no in-person interview for the Academic MS program. Offers of admission are made on a rolling basis starting in March. Finals decisions from admitted candidates are due by April 15.
• The selection of MS students admitted to DBDS is based on an individualized, holistic review of each application, including (but not limited to) the applicant’s academic record, the letters of recommendation, the statement of purpose, personal qualities and characteristics, and past accomplishments.

Distance Education MS in Biomedical Data Science

The Biomedical Data Science program offers a Honors Cooperative Program (HCP), a part-time, distance education Masters program. The HCP MS program is designed for working professionals, generally those employed in biomedical informatics or related fields. Other candidates may also apply. Note that the HCP MS is a regular MS degree awarded by Stanford University.

Students receive course content and interact via the Stanford Center for Professional Development (SCPD). It is  highly recommended  that candidates start by reviewing the information about this program on the  Stanford Online  website, especially their  HCP student handbook . Applicants are  strongly encouraged to consider starting as a Non-Degree Option student (either a single course, or a three course certificate). Taking at least one of the DBDS core courses before applying is recommended but not required.

Currently all of the curriculum content is available for fully-remote access. HCP MS students are allowed to attend class on campus if that is better for them. Remote access is not fully under DBDS’s control, and might change in the future; however, we would make every reasonable effort to accommodate alternatives if needed.

To learn more about our programs, consider attending the  Meet the Students Panel .

Our graduate curriculum is described  here . Candidates may wish to begin with SCPD Certificate program in Biomedical Data Science, or individual courses through the SCPD’s Non-Degree Option. Up to 18 units of academic credit from relevant Certificate programs may be transferred upon acceptance into the degree program. In addition, you can complete some prerequisite coursework through SCPD, such as a Computer Science Certificate.

Students spend on average of 3.5 years in the program. The program must be completed within five years.

Switching MS Programs

Requests to transfer from part-tIme (HCP) to full-time (Academic MS) are reviewed by the DBDS Executive Committee on a case-by-case basis. Final decisions are at DBDS’s discretion. Please note the following limitations (for students enrolling in the HCP program starting Fall 2020) :

• Students must  complete a minimum of two (2) quarters in the part-time program excluding summer quarter or enrollment as a non-degree option student, before requesting to transfer to full-time. Therefore, the soonest the transfer can be discussed and approved is during the first DBDS Exec meeting of the third quarter of the student in the HCP program
• Students must complete a minimum of 10 units of letter-graded courses that meet requirements for the DBDS MS degree before commencing their first full-time (Academic MS) quarter
• GPA will be considered as part of the request.
• Students can make a maximum of two (2) transfers during the program (e.g. transfer from part-time to full-time and back to part-time).
• Students should consider the availability of courses online before requesting to switch from full-time to part-time, especially if this may interfere with their ability to satisfy the requirements of the degree.

The Stanford Center for Professional Development sets the tuition for all of the Honors Cooperative Programs. There is a three unit minimum enrollment per academic quarter. Check the latest tuition and fees at the  Stanford Center for Professional Development website. The DBDS program does not set rates or policies or collect tuition.

Some employers will support tuition for students enrolled in graduate studies while employed. Check with your Human Resources department for programs and policies. Students in the HCP MS program are not eligible for funding from many US government fellowships and other scholarships due to the required research component of the awards. Many student loan programs require full-time registration status. DBDS does not provide financial aid for this program.

Review the information on the  Bioscience Application  website.

Complete the  Biosciences Application  (same as PhD) online. Applications are accepted most of the year, and students can start any quarter except Summer. The deadlines for HCP applications are specific to this degree program, and are listed  here .

Applications are accepted for admission each quarter except summer. The application deadlines are shown here:

Coterminal MS in Biomedical Data Science

The Biomedical Data Science program offers a coterminal Masters program for Stanford undergraduates.

Policies and Degree Requirements

The Registrar’s webpage on Coterminal Degree Programs is  here . Graduate Education website on coterminal degrees is  here .

The MS curriculum is described  here . Coterminal Masters students are not required to perform research rotations or submit a research project, although they are welcome to do so.

Please see the  prerequisites page. In addition, we recommend (but do not require) that you take at least one DBDS core course before applying.

We accept applications to the coterminal Masters program quarterly.  These application instructions are for the Coterminal Masters only.  The deadlines to submit your applications are listed in the table below. Letters of recommendation are required by the deadline.

If you lose your undergraduate status prior to the completion of the application for the coterminal MS, you must apply as a regular candidate to the DBDS program.

Application Procedure

Fill out the  Coterm on-line application . The application will ask you for:

• A Stanford Transcript
• GREs: Applicants to DBDS’s Coterminal MS program are not required to submit GRE scores.
• TOEFL:  The TOEFL is not required.
• Personal Statement (1-2 pages):  See  here .
• Enriching the Learning Community: Stanford University welcomes graduate applications from individuals with a broad range of experiences, interests, and backgrounds who would contribute to our community of scholars. We invite you to share the lived experiences, demonstrated values, perspectives, and/or activities that shape you as a scholar and would help you to make a distinctive contribution to Stanford University.
• Your Curriculum Vitae:  If you listed Awards and Publications on your CV, then you can skip the Awards and Publications question on the application.
• Two Letters of Recommendation:  You may submit more if you feel this enhances your chances of admission. The letters should come from faculty or others who are familiar with your academic/research activity.
• Prerequisites: We expect strong preparation of our prerequisites in order to make reasonable progress through our curriculum. Otherwise, please clearly indicate what your plan is to complete them, preferably prior to enrolling in DBDS. They will be reviewed on a case by case basis. The Registrar’s package contains the Preliminary Program Proposal Form; it is better to list all the proposed courses on the DBDS  Flow Sheet , and then just write “see flow sheet (attached)” on the Proposal Form. Please make sure you have a clear set of classes and schedule that will complete your prerequisites, your undergraduate degree requirements and graduate degree requirements. If you are uncertain, make your best estimate.  These instructions  (for current students) are also likely to be of use when applying.
• Additional Materials:  If you are submitting any additional materials, send them directly to the DBDS program at our Contact Address .
• Other:  Supplemental or additional department application requirements.

Decisions and Acceptance

In general, you will be notified by the end of the month in which you apply. If offered admission, you should reply by email to the offer.

Getting an Advisor

Upon acceptance into the program, you will be assigned a course advisor. You will revise your Program Proposal at this time. Please contact the DBDS program office if you need advice about coterminal status between acceptance and your first appointment with your course advisor.

Funding Sources

Access to financial aid and other options is very different for coterminal students and depends on the number of units and quarters as a registered student at Stanford.

Coterminal students have full access to undergraduate sources of financial aid until their twelfth quarter or four years of study. Coterminal students who have completed 180 units of are eligible for University fellowships and assistantships. However, many federal and private fellowships and assistantships are awarded only to students who have received the bachelors degree. Even after the conferral of the bachelors, there is no guarantee that a coterminal student will be awarded financial support via a RAship, TAship or fellowship.

Upon completion of the requirements for the bachelors, coterms may choose to obtain their bachelors degree early. However, all classes after conferral of the degree may only be counted towards the graduate degree. Please note, part of the strategy which allows coterms maximal flexibility in their course of study is their dual status as both undergraduates and graduate students.

You should definitely look at  our page for current coterm students . Also, it is highly recommended that you review our  Frequently Asked Questions  page

Personal Statement for applying in Biomedical Data Science

Instructions for writing your personal statement (statement of purpose).

You are required to submit a Personal Statement (Statement of Purpose) as part of the Graduate Application for either the MS or PhD degree.

Please note that the DBDS program focuses on the development  of novel computational and quantitative methods that can advance biomedicine. If your primary interest lies in the  application of such methods to pursue problems in a particular domain of biomedicine, then other Biosciences home programs are likely a better choice. The Admissions Committee will read your Personal Statement carefully to determine how well your aspirations align with the mission of the DBDS Training Program.

In your Personal Statement, please tell us how your schooling, work, research, and life experiences prepare you for study at DBDS, describe your current research interests and career goals, and explain how our training program will enable you to achieve them.

The Personal Statement should be 1-2 pages. Please do not append class projects, research proposals, draft manuscripts, published papers, posters, or other ancilliary materials.

Postdoctoral Training in Biomedical Data Science

Postdoctoral training is for those who already possess a doctoral level research degree (PhD, DSc), or professional degree (MD, DO, DDS).

• If you are interested in postdoctoral training which leads to an MS degree, then apply to our  Academic MS  program. (You could also apply to the PhD program if for some reason you wanted a second PhD, but we do not recommend this.)
• If you are looking for a postdoctoral research position without required classwork, then you should apply directly to the relevant faculty, generally in response to posted listings of postdoctoral positions. See the  general information  about postdoctoral training at Stanford. Also, see our  Resources for Postdocs page and our Faculty page.

Stanford offers an ACGME-approved fellowship in Clinical Informatics for board-eligible MDs. For more information, see the  main page for that fellowship .

Note that although there is some overlap in name, content, and personnel, the CI fellowship and DBDS graduate program are organizationally separate and serve different career goals. You may only apply to one of the two programs . The CI fellowship is for clinicians seeking further training in the broad area of applied clinical informatics; the DBDS program is for those seeking research training in quantitative and computational methods. Please review the materials for both programs and contact either program if you have questions.

Distance Education Programs in Biomedical Data Science including Certificate Program

In addition to the  distance education MS degree , DBDS offers a non-degree option of obtaining a certificate (three classes) or for taking individual classes. Students receive course content and interact via the Stanford Center for Professional Development (SCPD). All of the coursework is on-line; no time at Stanford is required. It is highly recommended that you start by reviewing the information on the SCPD  website, especially their  handbook  for non-degree option students. Information about any course can be found in Stanford’s  Explore Courses .

Certificate Program Eligibility and Prerequisites

The following are required for entry into the Certificate Program. Note that these prerequisite courses do not count towards the Certificate, even if taken at Stanford.

• A bachelor’s degree with a 3.0 (B) grade point average or better.
• One year of computer programming/software engineering coursework or equivalent experience. We recommend that students take the equivalent of Stanford’s CS 106A and CS 106B prior to entering the Certificate Program.
• One year of college biology.
• One year of calculus is required for some classes.
• Classwork in probability and statistics is a prerequisite for some classes.
• Some BIOMEDIN courses may have additional prerequisites. These are listed in Stanford’s catalog,  Explore Courses .

You need to achieve at least a B (3.0) in each Certificate class to continue in the program.

Student with good reasons may request waiver of these requirements through DBDS program staff.

Certificate in Biomedical Data Science: Data, Modeling and Analysis

Three courses are required for the Biomedical Data Science  Certificate . These courses are chosen from the following DBDS core courses.

• BIOMEDIN 210: Modeling Biomedical Systems: Ontology, Terminology, Problem Solving (Win quarter)
• BIOMEDIN 214: Representations and Algorithms for Computational Molecular Biology (Aut quarter)
• BIOMEDIN 215: Data Driven Medicine (Aut quarter)
• BIOMEDIN 217: Translational Bioinformatics (Win quarter)
• BIOMEDIN 260: Computational Methods for Biomedical Image Analysis (Spr quarter)

Individual Courses (Non-degree Option)

You can enroll in individual courses without pursuing a degree or certificate. You can use up to 18 Stanford units towards a degree (including those from a certificate) if you are later accepted into one of our degree programs.

You should apply directly through  SCPD , not DBDS or Biosciences.

See  here .

Biomedical Data Science for Stanford Medical Students

There several ways that Stanford medical students can be involved in DBDS-related activities. Some of these are integrated into the medical curriculum. Others involve applying to DBDS degree programs.

Scholarly Concentration

The Stanford medical curriculum provides medical training and an intellectual foundation to support future medical investigation through the required  Scholarly Concentrations . Stanford medical students interested in Biomedical Data Science can choose the Informatics and Data-Driven Medicine  concentration, one of the Foundation areas. These students take several classes in this area, including  BIOMEDIN 205 , where leading researchers from Stanford and the Bay Area present overviews of their work.

Medical Scholars

Medical students who want a more in-depth research experience are invited to participate in the  Medical Scholars  research program.

Graduate Programs (MS or PhD)

Medical students can apply to our MS or PhD programs. Follow  these procedures  for normal graduate applications and  these procedures  for MSTP students or applicants.

Postdoctoral Programs

Medical students can also apply to pursue either the MS or PhD degree after receiving their MD.

Biomedical Data Science for Stanford MSTP (Medical Scientist Training Program) students

For those already in the mstp program.

• You do rotations during the first two years (M1-2). When you join the DBDS PhD program during the Autumn quarter of your 3rd year, file a Graduate Authorization Petition (via Axess) by the second week of the quarter.
• You should request that the MSTP office send us a copy of your MSTP application.
• A unofficial copy of your Stanford transcript
• An up-to-date copy of your CV
• Your  personal statement (specifically for DBDS)
• One letter of recommendation from Stanford faculty
• The DBDS supplemental application form
• Note that GREs are not required, and there is no personal interview.

For current medical students applying to the MSTP program

• You can apply to the internal track of the MSTP and you also apply to DBDS through the standard Biosciences PhD procedure .
• MCATs can be supplied in place of the GREs (but strong performance on GRE could increase chance of acceptance in some cases).
• In-person interviews are typically early March.
• If you are not chosen by MSTP for funding, DBDS will consider you in the normal application pool with training grant funding through DBDS.

These instructions are for those currently enrolled in graduate study at Stanford (including medical students) who want to add our MS degree. However, if you are applying to DBDS for a degree to start after your current degree has been conferred, or if you are applying to DBDS to the PhD degree or the postdoctoral MS degree, then skip this page and follow the normal application instructions for the desired degree; note that generally you will have to apply in the Autumn to start in the following Autumn (or Summer).

You should submit  directly to us :

• A Graduate Authorization Petition (via Axess)
• Two letters of recommendation (have recommender send directly to us, or submit in sealed, signed envelope)
• An unofficial copy of your Stanford transcript and of any previous transcripts
• A 1-2 page  personal statement
• The DBDS  supplemental application form
• a DBDS  course flowsheet  with your proposed plan of study

Applications are accepted throughout the year. The deadlines to submit your applications are listed in the table below.

Biomedical Data Science for Stanford Undergraduates

The Biomedical Data Science Program does not offer an undergraduate major.

For students interested in an undergraduate major with an option to specialize in the area of Biomedical Data Science, see the Biomedical Computation  major.

Stanford undergraduates may choose to combine their major with the coterminal Masters degree. The Biomedical Data Science coterminal MS may be combined with many undergraduate majors; Computer Science, Biomedical Computation, Mathematical and Computational Science, Bioengineering, or any of the biological science programs offer the most efficient combination of the two degrees. See our webpage on the coterminal degree , and  the University rules .

Information for International Applicants

We welcome applications from international applicants. International applicants follow the same application process as other applicants, with additional rules and requirements listed here .

Required Academic Credentials

You need to hold a four-year bachelors degree in order to apply. The exact requirements vary by country and are listed on the Office of Graduate Admissions  International Applicants page .

Scores are required of all applicants whose first language is not English. Note that if  all  instruction for your bachelors or master degree program was in English, then the TOEFL is not required. See the  Biosciences Admissions page  for more details. Note that Stanford only accepts the TOEFL, not other tests of English.

We do not advise applicants about visas. The  Bechtel International Center  has information about how to maintain visas for international students. The US State Department has information about student and exchange visitor visas.

Please look at the webpage for the degree program (PhD or MS) to which you are applying. Unfortunately, funding for international students is quite limited, and you are encouraged to seek external funding. You should consider applying for Stanford’s  Knight-Hennessy Scholars program . Your home country may have programs to support study overseas. The  Fulbright program  funds international scholars. The Fogarty International Center maintains a  Directory of Funding Opportunities . The  Institute of International Education  has a search engine which will help you locate programs which fund international study.

For MS applicants: We have very occasionally had self-funded international MS students. You need to show funds equivalent to one year of tuition and board to meet the visa requirements.

NYU Center for Data Science

Harnessing Data’s Potential for the World

Master’s in Data Science

• Industry Concentration
• Admission Requirements
• Capstone Project
• Summer Research Initiative
• Financial Aid
• MS Admissions Ambassadors
• Summer Initiative

The  Fall 202 4   application deadline was Monday, January 22, 2024, 5pm ET.

The Fall 2024 MS Admissions Information Session took place Thursday, October 19 at 10am.

Please note that we do not have Spring Admissions for the MSDS.

Admission to NYU’s Master of Science in Data Science is extremely competitive. This speaks both to the popularity of the field of Data Science and to the very high calibre of students who we seek as part of our program.

Without exception, you must submit the following to support your application for admission:

• TOEFL or IELTS; however, TOEFL is preferred (Required for all applicants whose native language is not English and who have not received a university degree in an English-speaking country)
• Official college transcripts
• Three letters of recommendation (we prefer all letters on letterhead)
• Statement of Academic Purpose
• (optional) Personal History Statement
• (optional) GRE scores

For more information, visit the graduate schools  application resource center .

Educational Prerequisites

Successful applicants to the MSDS come from many different undergraduate backgrounds, including degrees in Statistics, Computer Science, Mathematics, Engineering, Economics, Business, Biology, Physics and Psychology. In the 2023 intake cycle, the average GPA was 3.80. Our students’ transcripts usually include As and Bs (only), and we expect stronger grades in more relevant subject matter (see below) from those coming from less selective institutions. Regardless of degree, we require specific and substantial knowledge of certain mathematical competencies, and some training in programming and basic computer science.

To be considered for the program, you will be required to have completed the following (or equivalents, e.g. MOOCs certification or course credit):

• Calculus I: limits, derivatives, series, integrals, etc.
• Linear Algebra
• Intro to Computer Science (or an equivalent “CS-101” programming course): We have no set requirements as regards specific languages, but we generally expect serious academic and/or professional experience with Python and/or R  at a minimum .
• One of Calculus II, Probability, Statistics, or an advanced physics, engineering, or econometrics course with heavy mathematical content

Preference is given to applicants with prior exposure to machine learning, computational statistics, data mining, large-scale scientific computing, operations research (either in an academic or professional context), as well as to applicants with significantly more mathematical and/or computer science training than the minimum requirements listed above.

Work Experience

Many of our students join us directly from undergraduate, but we also very much welcome evidence of relevant work experience—and clear employment goals once the MSDS is completed—in data science.  Past experience and career aspiration goals can be related to commercial industry, government, academia or some other sector.

Standardized Tests

GRE General Test is optional. If submitting, please note: we do not accept “out of date” scores (see FAQs here ); nor do we accept scores of other, similar tests.  

If submitting scores for the GRE General test with your application, please upload a PDF of the unofficial scores, which are made available upon completion of your test, to the “Additional Information Section” of your application. This is in addition to sending your official scores to the Graduate School of Arts and Science.

We also require evidence of proficiency with English as a second language for certain students who must provide it. For those students, we recommend a TOEFL score of at least 100 overall (and have strong preferences for better scores).

For additional information regarding standardized testing please visit the Graduate School of Arts and Science’s FAQ Page .

Three Letters of Recommendation

Recommendations for admitted students are invariably excellent, with references holding applicants in the highest esteem relative to other students or employees with whom they have interacted in the past several years. References from professors or employers who can comment directly and in a detailed way on the applicant’s case, aptitude for, and attitude to data science projects are treated with the most weight. Though not required, we prefer all letters on letterhead.

For additional information regarding letters of recommendation please visit the Graduate School of Arts and Science’s FAQ Page .

International Students

Answers to common questions that international student applicants may have can be found in the Graduate School of Arts & Science’s Application Resource Center . 

In particular, questions regarding what degree must an applicant have in order to enroll are addressed here . If you have further questions about your degree eligibility, please contact the GSAS Graduate Enrollment Services team at [email protected] . 

Information about international transcript evaluations and other information about being an international student at NYU can be found here .

Internal Transfers/Current NYU Students

We do not allow internal transfers from other NYU graduate programs. If you are a current NYU graduate student and you would like to be a part of the NYU Data Science MS program, please note that you are required to submit a new application.

Ready to Apply?

If your background meets the majority of these requirements, and you have a desire to develop the methods to harness the potential of data, then we encourage you to begin the application process. Please proceed to the Graduate School of Arts and Science webpage to apply for admission . 

Prior to starting your application please review the Graduate School of Arts and Science’s general application policies page .

For more questions, email us at  [email protected] .

Deferral Requests

The Center for Data Science will not approve a request for deferral of admission. If an admitted student wishes to delay enrollment, it will be necessary to turn down the offer of admission and reapply for admission the following year. A completely new application will be required. The new application will be considered along with all other applications at that later time.