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Center for Computational Biology

Computational Biology PhD

The main objective of the Computational Biology PhD is to train the next generation of scientists who are both passionate about exploring the interface of computation and biology, and committed to functioning at a high level in both computational and biological fields.

The program emphasizes multidisciplinary competency, interdisciplinary collaboration, and transdisciplinary research, and offers an integrated and customizable curriculum that consists of two semesters of didactic course work tailored to each student’s background and interests, research rotations with faculty mentors spanning computational biology’s core disciplines, and dissertation research jointly supervised by computational and biological faculty mentors.

The Computational Biology Graduate Group facilitates student immersion into UC Berkeley’s vibrant computational biology research community. Currently, the Group includes over 46 faculty from across 14 departments of the College of Letters and Science, the College of Engineering, the College of Natural Resources, and the School of Public Health. Many of these faculty are available as potential dissertation research advisors for Computational Biology PhD students, with more available for participation on doctoral committees.

The First Year

The time to degree (normative time) of the Computational Biology PhD is five years. The first year of the program emphasizes gaining competency in computational biology, the biological sciences, and the computational sciences (broadly construed). Since student backgrounds will vary widely, each student will work with faculty and student advisory committees to develop a program of study tailored to their background and interests. Specifically, all first-year students must:

• Perform three rotations with Core faculty (one rotation with a non-Core faculty is acceptable with advance approval)
• Complete course work requirements (see below)
• Complete a course in the Responsible Conduct of Research
• Attend the computational biology seminar series
• Complete experimental training (see below)

Laboratory Rotations

Entering students are required to complete three laboratory rotations during their first year in the program to seek out a Dissertation Advisor under whose supervision dissertation research will be conducted. Students should rotate with at least one computational Core faculty member and one experimental Core faculty member. Click here to view rotation policy. 

Course Work & Additional Requirements

Students must complete the following coursework in the first three (up to four) semesters. Courses must be taken for a grade and a grade of B or higher is required for a course to count towards degree progress:

• Fall and Spring semester of CMPBIO 293, Doctoral Seminar in Computational Biology
• A Responsible Conduct of Research course, most likely through the Department of Molecular and Cell Biology.
• STAT 201A & STAT 201B : Intro to Probability and Statistics at an Advanced Level. Note: Students who are offered admission and are not prepared to complete STAT 201A and 201B will be required to complete STAT 134 or PH 142 first.
• CS61A : The Structure and Interpretation of Computer Programs. Note: students with the equivalent background can replace this requirement with a more advanced CS course of their choosing.
• 3 elective courses relevant to the field of Computational Biology , one of which must be at the graduate level (see below for details).
• Attend the computational biology invited speaker seminar series. A schedule is circulated to all students by email and is available on the Center website. Starting with the 2023 entering class, CCB PhD students must enroll in CMPBIO 275: Computational Biology Seminar , which provides credit for this seminar series.
• 1) completion of a laboratory course at Berkeley with a minimum grade of B,
• 2) completion of a rotation in an experimental lab (w/ an experimental project), with a positive evaluation from the PI,
• a biological sciences undergraduate major with at least two upper division laboratory-based courses,
• a semester or equivalent of supervised undergraduate experimental laboratory-based research at a university,
• or previous paid or volunteer/internship work in an industry-based experimental laboratory.

Students are expected to develop a course plan for their program requirements and to consult with the Head Graduate Advisor before the Spring semester of their first year for formal approval (signature required). The course plan will take into account the student’s undergraduate training areas and goals for PhD research areas.

Satisfactory completion of first year requirements will be evaluated at the end of the spring semester of the first year. If requirements are satisfied, students will formally choose a Dissertation advisor from among the core faculty with whom they rotated and begin dissertation research.

Waivers: Students may request waivers for the specific courses STAT 201A, STAT 201B, and CS61A. In all cases of waivers, the student must take alternative courses in related areas so as to have six additional courses, as described above. For waiving out of STAT 201A/B, students can demonstrate they have completed the equivalent by passing a proctored assessment exam on Campus. For waiving out CS61A, the Head Graduate Advisor will evaluate student’s previous coursework based on the previous course’s syllabus and other course materials to determine equivalency.

Electives: Of the three electives, students are required to choose one course in each of the two following cluster areas:

• Cluster A (Biological Science) : These courses are defined as those for which the learning goals are primarily related to biology. This includes courses covering topics in molecular biology, genetics, evolution, environmental science, experimental methods, and human health. This category may also cover courses whose focus is on learning how to use bioinformatic tools to understand experimental data.
• Cluster B (Computational Sciences): These courses are defined as those for which the learning goals involve computing, inference, or mathematical modeling, broadly defined. This includes courses on algorithms, computing languages or structures, mathematical or probabilistic concepts, and statistics. This category would include courses whose focus is on biological applications of such topics.

In the below link we give some relevant such courses, but students can take courses beyond this list; for courses not on this list, the Head Graduate Advisor will determine to which cluster a course can be credited. For classes that have significant overlap between these two clusters, the department which offers the course may influence the decision of the HGA as to whether the course should be assigned to cluster A or B.

See below for some suggested courses in these categories:

Suggested Coursework Options

Second Year & Beyond

At the beginning of the fall of the second year, students begin full-time dissertation research in earnest under the supervision of their Dissertation advisor. It is anticipated that it will take students three (up to four) semesters to complete the 6 course requirement. Students are required to continue to participate annually in the computational biology seminar series.

Qualifying Examination

Students are expected to take and pass an oral Qualifying Examination (QE) by the end of the spring semester (June 15th) of their second year of graduate study. Students must present a written dissertation proposal to the QE committee no fewer than four weeks prior to the oral QE. The write-up should follow the format of an NIH-style grant proposal (i.e., it should include an abstract, background and significance, specific aims to be addressed (~3), and a research plan for addressing the aims) and must thoroughly discuss plans for research to be conducted in the dissertation lab. Click here for more details on the guidelines and format for the QE. Click here to view the rules for the composition of the committee and the form for declaring your committee.

Advancement to Candidacy

After successfully completing the QE, students will Advance to Candidacy. At this time, students select the members of their dissertation committee and submit this committee for approval to the Graduate Division. Students should endeavor to include a member whose research represents a complementary yet distinct area from that of the dissertation advisor (ie, biological vs computational, experimental vs theoretical) and that will be integrated in the student’s dissertation research. Click here to view the rules for the composition of the committee and the form for declaring your committee.

Meetings with the Dissertation Committee

After Advancing to Candidacy, students are expected to meet with their Dissertation Committee at least once each year.

Teaching Requirements

Computational Biology PhD students are required to teach at least two semesters (starting with Fall 2019 class), but may teach more. The requirement can be modified if the student has funding that does not allow teaching. Starting with the Fall 2019 class: At least one of those courses should require that you teach a section. Berkeley Connect or CMPBIO 293 can count towards one of the required semesters.

The Dissertation

Dissertation projects will represent scholarly, independent and novel research that contributes new knowledge to Computational Biology by integrating knowledge and methodologies from both the biological and computational sciences. Students must submit their dissertation by the May Graduate Division filing deadline (see Graduate Division for date) of their fifth–and final–year.

Special Requirements

Students will be required to present their research either orally or via a poster at the annual retreat beginning in their second year.

• Financial Support

The Computational Biology Graduate Group provides a competitive stipend (the stipend for 2023-24 is $43,363) as well as full payment of fees and non-resident tuition (which includes health care). Students maintaining satisfactory academic progress are provided full funding for five to five and a half years. The program supports students in the first year, while the PI/mentor provides support from the second year on. A portion of this support is in the form of salary from teaching assistance as a Graduate Student Instructor (GSI) in allied departments, such as Molecular and Cell Biology, Integrative Biology, Plant and Microbial Biology, Mathematics, Statistics or Computer Science. Teaching is part of the training of the program and most students will not teach more than two semesters, unless by choice.

Due to cost constraints, the program admits few international students; the average is two per year. Those admitted are also given full financial support (as noted above): stipend, fees and tuition.

Students are also strongly encouraged to apply for extramural fellowships for the proposal writing experience. There are a number of extramural fellowships that Berkeley students apply for that current applicants may find appealing. Please note that the NSF now only allows two submissions – once as an undergrad and once in grad school. The NSF funds students with potential, as opposed to specific research projects, so do not be concerned that you don’t know your grad school plans yet – just put together a good proposal! Although we make admissions offers before the fellowships results are released, all eligible students should take advantage of both opportunities to apply, as it’s a great opportunity and a great addition to a CV.

• National Science Foundation Graduate Research Fellowship (app deadlines in Oct)
• Hertz Foundation Fellowship (app deadline Oct)
• National Defense Science and Engineering Graduate Fellowship (app deadline in mid-Fall)
• DOE Computational Science Graduate Fellowship (Krell Institute) (app deadline in Jan)

CCB no longer requires the GRE for admission (neither general, nor subject). The GRE will not be seen by the review committee, even if sent to Berkeley.

PLEASE NOTE: The application deadline is Wednesday, November 30 , 2023, 8:59 PST/11:59 EST

If you would like to learn more about our program, you can watch informational YouTube videos from the past two UC Berkeley Graduate Diversity Admissions Fairs: 2021 recording & 2020 recording .

We invite applications from students with distinguished academic records, strong foundations in the basic biological, physical and computational sciences, as well as significant computer programming and research experience. Admission for the Computational Biology PhD is for the fall semester only, and Computational Biology does not offer a Master’s degree.

We are happy to answer any questions you may have, but please be sure to read this entire page first, as many of your questions will be answered below or on the Tips tab.

IMPORTANT : Please note that it is not possible to select a specific PhD advisor until the end of the first year in the program, so contacting individual faculty about openings in their laboratories will not increase your chances of being accepted into the program. You will have an opportunity to discuss your interests with relevant faculty if you are invited to interview in February.

Undergraduate Preparation

Minimum requirements for admission to graduate study:

• A bachelor’s degree or recognized equivalent from an accredited institution.
• Minimum GPA of 3.0.
• Undergraduate preparation reflecting a balance of training in computational biology’s core disciplines (biology, computer science, statistics/mathematics), for example, a single interdisciplinary major, such as computational biology or bioinformatics; a major in a core discipline and a combination of interdisciplinary course work and research experiences; or a double major in core disciplines.
• Basic research experience and aptitude are key considerations for admission, so evidence of research experience and letters of recommendation from faculty mentors attesting to the applicant’s research experience are of particular interest.
• GRE – NOT required or used for review .
• TOEFL scores for international students (see below for details).

Application Requirements

ALL materials, including letters, are due November 30, 2023 (8:59 PST). More information is provided and required as part of the online application, so please create an account and review the application before emailing with questions (and please set up an account well before the deadline):

• A completed graduate application: The online application opens in early or mid-September and is located on the Graduate Division website . Paper applications are not accepted. Please create your account and review the application well ahead of the submit date , as it will take time to complete and requests information not listed here.
• A nonrefundable application fee: The fee must be paid using a major credit card and is not refundable. For US citizens and permanent residents, the fee is $135; US citizens and permanent residents may request a fee waiver as part of the online application. For all other students (international) the fee is $155 (no waivers, no exceptions). Graduate Admissions manages the fee, not the program, so please contact them with questions.
• Three letters of recommendation, minimum (up to five are accepted): Letters of recommendation must be submitted online as part of the Graduate Division’s application process. Letters are also due November 30, so please inform your recommenders of this deadline and give them sufficient advance notice. It is your responsibility to monitor the status of your letters of recommendation (sending prompts, as necessary) in the online system.
• Transcripts: Unofficial copies of all relevant transcripts, uploaded as part of the online application (see application for details). Scanned copies of official transcripts are strongly preferred, as transcripts must include applicant and institution name and degree goal and should be easy for the reviewers to read (print-outs from online personal schedules can be hard to read and transcripts without your name and the institution name cannot be used for review). Do not send via mail official transcripts to Grad Division or Computational Biology, they will be discarded.
• Essays: Follow links to view descriptions of what these essays should include ( Statement of Purpose [2-3 pages], Personal Statement [1-2 pages]). Also review Tips tab for formatting advice.
• (Highly recommended) Applicants should consider applying for extramural funding, such as NSF Fellowships. These are amazing opportunities and the application processes are great preparation for graduate studies. Please see Financial Support tab.
• Read and follow all of the “Application Tips” listed on the last tab. This ensures that everything goes smoothly and you make a good impression on the faculty reviewing your file.

The GRE general test is not required. GRE subject tests are not required. GRE scores will not be a determining factor for application review and admission, and will NOT be seen by the CCB admissions committee. While we do not encourage anyone to take the exam, in case you decide to apply to a different program at Berkeley that does require them: the UC Berkeley school code is 4833; department codes are unnecessary. As long as the scores are sent to UC Berkeley, they will be received by any program you apply to on campus.

TOEFL/IELTS

Adequate proficiency in English must be demonstrated by those applicants applying from countries where English is not the official language. There are two standardized tests you may take: the Test of English as a Foreign Language (TOEFL), and the International English Language Testing System (IELTS). TOEFL minimum passing scores are 90 for the  Internet-based test (IBT) , and 570 for the paper-based format (PBT) . The TOEFL may be waived if an international student has completed at least one year of full-time academic course work with grades of B or better while in residence at a U.S. university (transcript will be required). Please click here for more information .

Application Deadlines

The Application Deadline is 8:59 pm Pacific Standard Time, November 30, 2023 . The application will lock at 9pm PST, precisely. All materials must be received by the deadline. While rec letters can continue to be submitted and received after the deadline, the committee meets in early December and will review incomplete applications. TOEFL tests should be taken by or before the deadline, but self-reported scores are acceptable for review while the official scores are being processed. All submitted applications will be reviewed, even if materials are missing, but it may impact the evaluation of the application.

It is your responsibility to ensure and verify that your application materials are submitted in a timely manner. Please be sure to hit the submit button when you have completed the application and to monitor the status of your letters of recommendation (sending prompts, as necessary). Please include the statement of purpose and personal statement in the online application. While you can upload a CV, please DO NOT upload entire publications or papers. Please DO NOT send paper résumés, separate folders of information, or articles via mail. They will be discarded unread.

The Computational Biology Interview Visit dates will be: February 25-27, 2024

Top applicants who are being considered for admission will be invited to visit campus for interviews with faculty. Invitations will be made by early January. Students are expected to stay for the entire event, arriving in Berkeley by 5:30pm on the first day and leaving the evening of the final day. In the application, you must provide the names of between 7-10 faculty from the Computational Biology website with whom you are interested in conducting research or performing rotations. This helps route your application to our reviewers and facilitates the interview scheduling process. An invitation is not a guarantee of admission.

International students may be interviewed virtually, as flights are often prohibitively expensive.

Tips for the Application Process

Uploaded Documents: Be sure to put your name and type of essay on your essays ( Statement of Purpose [2-3 pages], Personal Statement [1-2 pages]) as a header or before the text, whether you use the text box or upload a PDF or Word doc. There is no minimum length on either essay, but 3 pages maximum is suggested. The Statement of Purpose should describe your research and educational background and aspirations. The Personal Statement can include personal achievements not necessarily related to research, barriers you’ve had to overcome, mentoring and volunteering activities, things that make you unique and demonstrate the qualities you will bring to the program.

Letters of Recommendation: should be from persons who have supervised your research or academic work and who can evaluate your intellectual ability, creativity, leadership potential and promise for productive scholarship. If lab supervision was provided by a postdoc or graduate student, the letter should carry the signature or support of the faculty member in charge of the research project. Note: the application can be submitted before all of the recommenders have completed their letters. It is your responsibility to keep track of your recommender’s progress through the online system. Be sure to send reminders if your recommenders do not submit their letters.

Extramural fellowships: it is to your benefit to apply for fellowships as they may facilitate entry into the lab of your choice, are a great addition to your CV and often provide higher stipends. Do not allow concerns about coming up with a research proposal before joining a lab prevent you from applying. The fellowships are looking for research potential and proposal writing skills and will not hold you to specific research projects once you have started graduate school.

Calculating GPA: Schools can differ in how they assign grades and calculate grade point averages, so it may be difficult for this office to offer advice. The best resource for calculating the GPA for your school is to check the back of the official transcripts where a guide is often provided or use an online tool. There are free online GPA conversion tools that can be found via an internet search.

Faculty Contact/Interests: Please be sure to list faculty that interest you as part of the online application. You are not required to contact any faculty in advance, nor will it assist with admission, but are welcome to if you wish to learn more about their research.

Submitting the application: To avoid the possibility of computer problems on either side, it is NOT advisable to wait until the last day to start and/or submit your application. It is not unusual for the application system to have difficulties during times of heavy traffic. However, there is no need to submit the application too early. No application will be reviewed before the deadline.

Visits: We only arrange one campus visit for recruitment purposes. If you are interested in visiting the campus and meeting with faculty before the application deadline, you are welcome to do so on your own time (we will be unable to assist).

Name: Please double check that you have entered your first and last names in the correct fields. This is our first impression of you as a candidate, so you do want to get your name correct! Be sure to put your name on any documents that you upload (Statement of Purpose, Personal Statement).

California Residency: You are not considered a resident if you hope to enter our program in the Fall, but have never lived in California before or are here on a visa. So, please do not mark “resident” on the application in anticipation of admission. You must have lived in California previously, and be a US citizen or Permanent Resident, to be a resident.

Faculty Leadership Head Graduate Advisor and Chair for the PhD & DE John Huelsenbeck ( [email protected] )

Associate Head Graduate Advisor for PhD & DE Liana Lareau ( [email protected] )

Equity Advisor Rasmus Nielsen ( [email protected] )

Director of CCB Elizabeth Purdom ( [email protected] )

Core PhD & DE Faculty ( link )

Staff support Student Services Advisor (GSAO): Kate Chase ( [email protected] )

• Open positions
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Information for prospective Ph.D. students in Computational Biology or Bioinformatics

The Ph.D. programs in Computational Biology at Johns Hopkins University span four Departments and a wide range of research topics. Our programs provide interdisciplinary training in computational and quantitative approaches to scientific problems that include questions in genomics, medicine, genome engineering, sequencing technology, molecular biology, genetics, and others.

Our students are actively involved in high-profile research, and have developed very widely-used bioinformatics software systems such as Bowtie , Tophat , and Cufflinks . and the more-recent systems HISAT and Stringtie (for RNA-seq alignment and assembly) and Kraken (for metagenomic sequence analysis). The work they do with Hopkins faculty prepares them to go on to postdoctoral and tenure track faculty positions at top-ranked universities including (in recent years) Harvard, the University of Washington, Carnegie Mellon, the University of Maryland, and Brown.

Students in computational biology at Hopkins can enroll in one of four different Ph.D. programs. These include Biomedical Engineering, ranked #1 in the nation; Biostatistics, also ranked #1 in the nation; Biology, ranked #6 in the nation; and the rapidly growing Computer Science Department, ranked #23 in the nation. Hopkins is also ranked #4 in the nation in Bioinformatics, a ranking that just started appearing in 2022.

CCB faculty have appointments in each of these programs, and some of us maintain appointments in multiple programs. To determine which program fits your interests and background, browse the course lists below. Each program has a separate application process; please apply specifically to the departments you're interested in. Applications to multiple programs are permitted, but if you're not certain, we encourage you to contact potential faculty advisors before you apply. Wherever you apply, make it clear that your interest is Computational Biology.

Sample Course Offerings for Ph.D. students in Computational Biology

Department of biomedical engineering, whiting school of engineering.

The Johns Hopkins Department of Biomedical Engineering (BME), widely regarded as the top program of its kind in the world and ranked #1 in the nation by U.S. News , is dedicated to solving important scientific problems at the intersection of multiple disciplines and that have the potential to make a significant impact on medicine and health. At the intersection of inquiry and discovery, the department integrates biology, medicine, and engineering and draws upon the considerable strengths and talents of the Johns Hopkins Schools of Engineering and Medicine. See the BME Ph.D. program website for many details.

Department of Computer Science, Whiting School of Engineering

The faculty represent a broad spectrum of disciplines encompassing core computer science and many cross-disciplinary areas including Computational Biology and Medicine, Information Security, Machine Learning, Data Intensive Computing, Computer-Integrated Surgery, and Natural Language Processing.

Ph.D. program

A total of 8 courses are required, and a typical load is 3 courses per semester. See the CS Department website for details. For a look at courses that might be included in Ph.D. training, see this page , though note that it is not a comprehensive list. For the Computer Science Ph.D., 2 out of the required 8 classes can be taken outside the Department. These may include any of the courses in the BME, Biostatistics, and Biology programs listed on this page.

Department of Biostatistics, Bloomberg School of Public Health

Johns Hopkins Biostatistics is the oldest department of its kind in the world and has long been considered as one of the best. In 2022, it was ranked #1 in the nation by U.S. News .

All students in the Biostatistics Ph.D. program have to complete the core requirements:

• A two-year sequence on biostatistical methodology (140.751-756)
• A two-year sequence on probability and the foundations and theory of statistical science (550.620-621, 140.673-674, 140.771-772);
• Principles of Epidemiology (340.601)

In addition, students in computational biology might take:

• 140.776.01 Statistical Computing (3 credits)
• 140.638.01 Analysis of Biological Sequences (3 credits)
• 140.644.01 Statistica machine learning: methods, theory, and applications (4 credits)
• 140.688.01 Statistics for Genomics (3 credits)

Further courses might include 2-3 courses in Computer Science, BME, or Biology listed on this page.

Department of Biology, Krieger School of Arts and Sciences

The Hopkins Biology Graduate Program, founded in 1876, is the oldest Biology graduate school in the country. People like Thomas Morgan, E. B. Wilson, Edwin Conklin and Ross Harrison, were part of the initial graduate classes when the program was first founded. Hopkins is ranked #6 in the nation in Biological Sciences by U.S. News

Quantitative and computational biology are an integral part of the CMDB training program. During the first semester students attend Quantitative Biology Bootcamp, a one week intensive course in using computational tools and programming for biological data analysis. Two of our core courses - Graduate Biophysical Chemistry and Genomes and Development - each have an associated computational lab component.

Ph.D. in Cell, Molecular, Developmental Biology, and Biophysics (CMDB):

The CMDB core includes the following courses:

• 020.607 Quantitative Biology Bootcamp
• 020.674 Graduate Biophysical Chemistry
• 020.686 Advanced Cell Biology
• 020.637 Genomes and Development
• 020.668 Advanced Molecular Biology
• 020.606 Molecular Evolution
• 020.620 Stem Cells
• 020.630 Human Genetics
• 020.640 Epigenetics & Chromosome Dynamics
• 020.650 Eukaryotic Molecular Biology
• 020.644 RNA

Students in computational biology can use their electives to take more computationally intensive courses. You have considerable flexibility to design a program of study with your Ph.D. advisor.

The Center for Computational Biology at Johns Hopkins University

Graduate Programs

Computational biology.

The Center for Computational Molecular Biology (CCMB) offers Ph.D. degrees in Computational Biology to train the next generation of scientists to perform cutting edge research in the multidisciplinary field of Computational Biology.

During the course of their Ph.D. studies students will develop and apply novel computational, mathematical , and statistical techniques to problems in the life sciences. Students in this program must achieve mastery in three areas - computational science, molecular biology, and probability and statistical inference - through a common core of studies that spans and integrates these areas.

The Ph.D. program in Computational Biology draws on course offerings from the disciplines of the Center’s Core faculty members. These areas are Applied Mathematics, Computer Science, the Division of Biology and Medicine, the Center for Biomedical Informatics, and the School of Public Health. Our faculty and Director of Graduate Studies work with each student to develop the best plan of coursework and research rotations to meet the student’s goals in their research focus and satisfy the University’s requirements for graduation.

Applicants should state a preference for at least one of these areas in their personal statement or elsewhere in their application. In addition, students interested in the intersection of Applied Mathematics and Computational Biology are encouraged to apply directly to the  Applied Mathematics Ph.D. program , and also to contact relevant  CCMB faculty members .

Our Ph.D. program assumes the following prerequisites: mathematics through intermediate calculus, linear algebra and discrete mathematics, demonstrated programming skill, and at least one undergraduate course in chemistry and in molecular biology. Exceptional strengths in one area may compensate for limited background in other areas, but some proficiency across the disciplines must be evident for admission.

Additional Resources

CCMB computing resources include a set of multiprocessor computer clusters and data storage servers with 392 processors. The CCMB Cluster is the largest dedicated computing system on campus for computational biology and bioinformatics applications. See also answers to  frequently asked questions .

Application Information

Application requirements, gre subject:.

Not required

GRE General:

Personal statement:.

Applicants will be asked a series of short form questions regarding their interest in computational biology, their research experiences, and their goals for the future. 1) Describe the life experiences that inspired you to pursue a career in science. 2) Describe at least one research experience you have had that prepared you intellectually/ scientifically for a career in computational biology. 3) Explain at least one challenge you have overcome in life or research to pursue a scientific career and what you have learned from this experience. 4) Discuss any broader impacts that you have had on your community (e.g. family, educational institution, or broader community). 5) Why would you like to pursue your PhD in the Brown CCMB program? (Include at least two faculty members who you would like to work with at Brown and why.)

Dates/Deadlines

Application deadline, completion requirements.

Six graduate–level courses, two eight–week laboratory rotations, preliminary research presentation, dissertation, oral defense

Contact and Location

Center for computational molecular biology, location address, mailing address.

• Program Faculty
• Program Handbook
• Graduate School Handbook

Ph.D. in Computational Biology and Bioinformatics

General info.

• Faculty working with students: 60
• Students: 29
• Part time study available: No
• Application Terms: Fall
• Application Deadline: November 30

Monica Franklin Program Coordinator CBB Graduate Program Duke University Box 90090 Durham, NC 27708

Phone: 919-668-1049

Email: [email protected]

Website:  https://medschool.duke.edu/education/biomedical-phd-programs/computational-biology-and-bioinformatics-program

Program Description

The mission of the Graduate Program in Computational Biology and Bioinformatics (CBB) is to train predoctoral students to become leaders at the interdisciplinary intersection of quantitative and biomedical sciences. The program provides rigorous training in quantitative approaches from computer science, statistics, mathematics, physics, and engineering that enable its students to successfully address contemporary challenges across biology and medicine.  CBB trains students who have an interest and aptitude in both the computational and biological sciences. During their time in the program, students develop expertise in one or more quantitative areas, as well as in the specific biological area on which their research focuses.

Certificate in CBB

For students enrolled in other Ph.D. or masters programs of participating departments, the program also offers the opportunity to pursue a certificate in CBB. Students qualify for a CBB certificate by successfully completing two core courses plus an additional CBB course. Registration for the Computational Biology seminar every semester except the semester of graduation is also required.

• Computational Biology and Bioinformatics: PhD Admissions and Enrollment Statistics
• Computational Biology and Bioinformatics: PhD Completion Rate Statistics
• Computational Biology and Bioinformatics: PhD Time to Degree Statistics
• Computational Biology and Bioinformatics: PhD Career Outcomes Statistics

Application Information

Application Terms Available:  Fall

Application Deadline:  November 30

Graduate School Application Requirements See the Application Instructions page for important details about each Graduate School requirement.

• Transcripts: Unofficial transcripts required with application submission; official transcripts required upon admission
• Letters of Recommendation: 3 Required
• Statement of Purpose: Required
• Résumé: Required
• GRE Scores: GRE General (Optional)
• English Language Exam: TOEFL, IELTS, or Duolingo English Test required* for applicants whose first language is not English *test waiver may apply for some applicants
• GPA: Undergraduate GPA calculated on 4.0 scale required

Department-Specific Application Requirements (submitted through online application)

Writing Sample None required

Additional Components Optional Video Essay: How would a Duke PhD training experience help you achieve your academic and professional goals? Max video length 2 minutes; record externally and provide URL in application.

We strongly encourage you to review additional department-specific application guidance from the program to which you are applying: Departmental Application Guidance

List of Graduate School Programs and Degrees

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Computational biology and bioinformatics.

MS Bioinformatics Program   |   PhD Bioinformatics Program   |   Online Application   |   Pre-Application

The study of bioinformatics and computational biology in the School of Biological Sciences includes the areas of development of new computational methods for studying organization and evolution of genes and genomes, computational approaches to macromolecular structure and dynamics, comparative evolutionary genomics, and prediction and analysis of structure.

The School of Biological Sciences at Georgia Tech proposed and established a professional Master of Science in Bioinformatics degree program in 1999-the first of its kind in the United States. The interdisciplinary program consists of unique combination of courses. The graduates are taught with the equal strength to several scientific disciplines and are prepared for further successful work in industry or academy.

Georgia Tech is now broadening its scope to include a formal PHD program in bioinformatics and computational biology. To further strengthen teaching and research collaborations between the faculty and participating in this program, the Georgia Tech Center for Bioinformatics and Computational Biology has been recently formed. Seminars, symposia, meetings and events also include participating faculty from Emory University and University of Georgia.

Faculty in this focus area

Mark Borodovsky Regents' Professor Department of Biomedical Engineering

Sam Brown Professor

Leonid Bunimovich Regents' Professor of Mathematics

Yuhong Fan Associate Professor and Georgia Research Alliance Distinguished Scholar

Greg Gibson Regents Professor, Tom and Marie Patton Chair in Biological Sciences, Director of the Center for Integrative Genomics, and member of the Petit Institute for Bioengineering and Bioscience

Brian Hammer Associate Professor

King Jordan Professor and Director, Bioinformatics Graduate Program

Kostas Konstantinidis Assistant Professor in the School of Civil and Environmental Engineering

Joel Kostka Professor and Associate Chair of Research

Joe Lachance Associate Professor and Director, GAANN Training Grant

John McDonald Professor

Patrick McGrath Associate Professor

Farzaneh Najafi Assistant Professor

William Ratcliff Associate Professor and Co-Director of the Interdisciplinary Ph.D. in Quantitative Biosciences

Jeffrey Skolnick Regents' Professor; Mary and Maisie Gibson Chair & GRA Eminent Scholar in Computational Systems Biology

Alberto Stolfi Assistant Professor

Francesca Storici Professor and Associate Chair for Graduate Education

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Computational Biology PhD

Under the auspices of the Center for Computational Biology, the Computational Biology Graduate Group offers the PhD in Computational Biology as well as the Designated Emphasis in Computational and Genomic Biology, a specialization for doctoral students in associated programs. The PhD is concerned with advancing knowledge at the interface of the computational and biological sciences and is therefore intended for students who are passionate about being high functioning in both fields. The designated emphasis augments disciplinary training with a solid foundation in the different facets of genomic research and provides students with the skills needed to collaborate across disciplinary boundaries to solve a wide range of computational biology and genomic problems.

Contact Info

[email protected]

108 Stanley Hall

Berkeley, CA 94720

At a Glance

Department(s)

Computational Biology Graduate Group

Admit Term(s)

Application Deadline

November 30, 2023

Degree Type(s)

Doctoral / PhD

Degree Awarded

GRE Requirements

Welcome to the MIT Computational and Systems Biology PhD Program (CSB)

The Ph.D. program seeks to train a new breed of quantitative biologists who can take advantage of technologies at the leading edge of science and engineering to tackle fundamental and applied problems in biology. Our students acquire: (i) a background in modern molecular/cell biology; (ii) a foundation in quantitative/engineering disciplines to enable them to create new technologies as well as apply existing methods; and (iii) exposure to subjects emphasizing the application of quantitative approaches to biological problems.  Our program and courses emphasize the logic of scientific discovery rather than mastering a specific set of skills or facts.  The program includes teaching experience during one semester of the second year.  It prepares students with the tools needed to succeed in a variety of academic and non-academic careers.

The program is highly selective with typical class sizes 8 to 10 students. About half of our graduate students are women, about one-quarter are international students, and about 10% are under-represented minorities.

Students complete most coursework during the first year, while exploring research opportunities through 1- or 2-month research rotations.  A faculty academic advisor assigned in the first year provides guidance and advice. Students choose a research advisor in spring or early summer of year 1 and develop a Ph.D. research project in with their advisor and input from a thesis committee chosen by the student.

Average time to graduation is 5½ years. 

The Program in CSB is committed to increasing opportunities for under-represented minority graduate students and students who have experienced financial hardship or disability.

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Even before she turned 20, Liyam Chitayat began her doctorate at MIT, one of the leading academic research institutions in the US and the world, and won the Hertz Award for Research Excellence - the most prest...

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Berkeley Berkeley Academic Guide: Academic Guide 2023-24

Computational biology.

About the Program

Under the auspices of the Center for Computational Biology, the Computational Biology Graduate Group offers the PhD in Computational Biology as well as the Designated Emphasis in Computational and Genomic Biology, a specialization for doctoral students in associated programs. The PhD is concerned with advancing knowledge at the interface of the computational and biological sciences and is therefore intended for students who are passionate about being high functioning in both fields. The designated emphasis augments disciplinary training with a solid foundation in the different facets of genomic research and provides students with the skills needed to collaborate across disciplinary boundaries to solve a wide range of computational biology and genomic problems.

Visit Group Website

Admission to the University

Applying for graduate admission.

Thank you for considering UC Berkeley for graduate study! UC Berkeley offers more than 120 graduate programs representing the breadth and depth of interdisciplinary scholarship. A complete list of graduate academic departments, degrees offered, and application deadlines can be found on the Graduate Division website .

Prospective students must submit an online application to be considered for admission, in addition to any supplemental materials specific to the program for which they are applying. The online application can be found on the Graduate Division website .

Admission Requirements

The minimum graduate admission requirements are:

A bachelor’s degree or recognized equivalent from an accredited institution;

A satisfactory scholastic average, usually a minimum grade-point average (GPA) of 3.0 (B) on a 4.0 scale; and

Enough undergraduate training to do graduate work in your chosen field.

For a list of requirements to complete your graduate application, please see the Graduate Division’s Admissions Requirements page . It is also important to check with the program or department of interest, as they may have additional requirements specific to their program of study and degree. Department contact information can be found here .

Where to apply?

Visit the Berkeley Graduate Division application page .

Admission to the Program

Applicants for the Computational Biology PhD are expected to have a strong foundation in relevant stem fields, achieved by coursework in at least two computational biology subfields (including, but not limited to, advanced topics in biology, computer science, mathematics, statistics). Typical students admitted to the program have demonstrated outstanding potential as a research scientist and have clear academic aptitude in multiple disciplines, as well as excellent communication skills. This is assessed based on research experience, coursework & grades, essays, personal background, and letters of recommendation. Three letters of recommendation are required, but up to five can be submitted. The GRE is no longer accepted or used as part of the review (this includes both the general and subject exams). The program does *not* offer a Masters degree in Computational Biology.

Doctoral Degree Requirements

Normative time requirements, normative time to advancement: two years.

Please refer to the PhD page on the CCB website for the most up-to-date requirements and information.

Year 1 Students perform three laboratory rotations with the chief aim of identifying a research area and thesis laboratory. They also take courses to advance their knowledge in their area of expertise or fill in gaps in foundational knowledge. With guidance from the program, students are expected to complete six total graded courses by the end of the second year (not including the Doc Sem or Ethics course). Please see the program's website for more detailed course and curriculum requirements.

Year 2 Students attend seminars, complete course requirements, and prepare a dissertation prospectus in preparation for their PhD oral qualifying examination. With the successful passing of the orals, students select their thesis committee and advance to candidacy for the PhD degree.

Normative Time in Candidacy: Three years

Years 3 to 5 Students undertake research for the PhD dissertation under a three or four-person committee in charge of their research and dissertation. Students conduct original laboratory research and then write the dissertation based on the results of this research. On completion of the research and approval of the dissertation by the committee, the students are awarded the doctorate.

Total Normative Time: 5-5.5 years

Time to advancement, lab rotations.

Students conduct three 10-week laboratory rotations in the first year. The thesis lab, where dissertation research will take place, is chosen at the end of the third rotation in late April/early May.

Qualifying Examination

The qualifying examination will evaluate a student’s depth of knowledge in his or her research area, breadth of knowledge in fundamentals of computational biology, ability to formulate a research plan, and critical thinking. The QE prospectus will include a description of the specific research problem that will serve as a framework for the QE committee members to probe the student’s foundational knowledge in the field and area of research. Proposals will be written in the manner of an NIH-style grant proposal. The prospectus must be completed and submitted to the chair no fewer than four weeks prior to the oral qualifying examination. Students are expected to pass the qualifying examination by the end of the fourth semester in the program.

Time in Candidacy

Advancement.

After passing the qualifying exam by the end of the second year, students have until the beginning of the fifth semester to select a thesis committee and submit the Advancement to Candidacy paperwork to the Graduate Division.

Dissertation

Primary dissertation research is conducted in years 3-5/5.5. Requirements for the dissertation are decided in consultation with the thesis advisor and thesis committee members. To this end, students are required to have yearly thesis committee meetings with the committee after advancing to candidacy.

Dissertation Presentation/Finishing Talk

There is no formal defense of the completed dissertation; however, students are expected to publicly present a talk about their dissertation research in their final year.

Required Professional Development

Presentations.

All computational biology students are expected to attend the annual retreat, and will regularly present research talks there. They are also encouraged to attend national and international conferences to present research.

Computational biology students are required to teach for one or two semesters (either one semester at 50% (20hrs/wk) or two semesters at 25% (10hrs/wk)) and may teach more. The requirement can be modified if the student has funding that does not allow teaching.

Designated Emphasis Requirements

Curriculum/coursework.

Please refer to the DE page on the CCB website for the most up-to-date requirements and information.

The DE curriculum consists of one semester of the Doctoral Seminar in computational biology (CMPBIO 293, offered Fall & Spring) taken before the qualifying exam, plus three courses, one each from the three broad areas listed below, which may be independent from or an integral part of a student’s Associated Program. The three courses should be taken in different departments, only one of which may be the student’s home program. These requirements must be fulfilled with coursework taken with a grade of B or better while the student is enrolled as a graduate student at UC Berkeley. S/U graded courses do not count . See below for recommended coursework.

Students do not need to complete all of the course requirements prior to the application or the qualifying exam. The Doctoral Seminar does not need to be taken in order, ie either Fall or Spring are ok, but should be prior to or in the same semester as the Qualifying Exam. The DE will be rescinded if coursework has not been completed upon graduation (students should report their progress each year to the DE advisor, especially if they wish to change one of the courses they listed for the requirement).

• Computer Science and Engineering: A single course at the level of CS61A or higher will fulfill this requirement. Students can also take CS 88 (as an alternative to CS61A), though depending on their background, Data 8 may be necessary to complete this course. Students with a more advanced background are recommended to take a higher level CS course to fulfill the requirement.
• Biostatistics, Mathematics and Statistics: A single course at the level of Stat 131A, 133, 134, or 135 or higher will fulfill this requirement. Students with a more advanced background are recommended to take one of either Stat 201A & 201B or a higher level course to fulfill the requirement. Statistics or probability courses from other departments may be able to fulfill this requirement with prior approval of the program.
• Biology: please select an appropriate biology course from the list linked below (not up-to-date), or choose a course from current course listings.
• Computational Biology: CMPBIO C293, Doctoral Seminar, offered Fall & Spring.

More information, including a link to pre-approved courses, can be found on the CCB website .

Qualifying Examination and Dissertation

The qualifying examination and dissertation committees must include at least one (more is fine) Core faculty members from the Computational Biology Graduate Group. The faculty member(s) may serve any role on the committee from Chair to ASR. The Qualifying Examination must include examination of knowledge within the area of Computational and Genomic Biology. The Comp Bio Doctoral Seminar must be completed before the QE, as it will be important preparation for the exam.

Seminars & Retreat

Students must attend the annual Computational Biology Retreat (generally held in November) as well as regular CCB Seminar Series , or equivalent, as designated by the Curriculum Committee. Students are also strongly encouraged to attend or volunteer with program events during Orientation, Recruitment, Symposia, etc. Available travel funds will be dependent upon participation.

CMPBIO 201 Classics in Computational Biology 3 Units

Terms offered: Fall 2015, Fall 2014, Fall 2013 Research project and approaches in computational biology. An introducton to the diverse ways biological problems are investigated computationally through critical evaluation of the classics and recent peer-reviewed literature. This is the core course required of all Computational Biology graduate students. Classics in Computational Biology: Read More [+]

Rules & Requirements

Prerequisites: Acceptance in the Computational Biology Phd program; consent of instructor

Hours & Format

Fall and/or spring: 15 weeks - 1 hour of lecture and 2 hours of discussion per week

Additional Format: One hour of Lecture and Two hours of Discussion per week for 15 weeks.

Additional Details

Subject/Course Level: Computational Biology/Graduate

Grading: Letter grade.

Classics in Computational Biology: Read Less [-]

CMPBIO C210 Introduction to Quantitative Methods In Biology 4 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course provides a fast-paced introduction to a variety of quantitative methods used in biology and their mathematical underpinnings. While no topic will be covered in depth, the course will provide an overview of several different topics commonly encountered in modern biological research including differential equations and systems of differential equations, a review of basic concepts in linear algebra, an introduction to probability theory, Markov chains, maximum likelihood and Bayesian estimation, measures of statistical confidence, hypothesis testing and model choice, permutation and simulation, and several topics in statistics and machine learning including regression analyses, clustering, and principal component analyses. Introduction to Quantitative Methods In Biology: Read More [+]

Objectives & Outcomes

Student Learning Outcomes: Ability to calculate means and variances for a sample and relate it to expectations and variances of a random variable. Ability to calculate probabilities of discrete events using simple counting techniques, addition of probabilities of mutually exclusive events, multiplication of probabilities of independent events, the definition of conditional probability, the law of total probability, and Bayes’ formula, and familiarity with the use of such calculations to understand biological relationships. Ability to carry out various procedures for data visualization in R. Ability to classify states in discrete time Markov chains, and to calculate transition probabilities and stationary distributions for simple discrete time, finite state-space Markov chains, and an understanding of the modeling of evolutionary processes as Markov chains. Ability to define likelihood functions for simple examples based on standard random variables. Ability to implement simple statistical models in R and to use simple permutation procedures to quantify uncertainty. Ability to implement standard and logistic regression models with multiple covariates in R. Ability to manipulate matrices using multiplication and addition. Ability to model simple relationships between biological variables using differential equations. Ability to work in a Unix environment and manipulating files in Unix. An understanding of basic probability theory including some of the standard univariate random variables, such as the binomial, geometric, exponential, and normal distribution, and how these variables can be used to model biological systems. An understanding of powers of matrices and the inverse of a matrix. An understanding of sampling and sampling variance. An understanding of the principles used for point estimation, hypothesis testing, and the formation of confidence intervals and credible intervals. Familiarity with ANOVA and ability to implementation it in R. Familiarity with PCA, other methods of clustering, and their implementation in R. Familiarity with basic differential equations and their solutions. Familiarity with covariance, correlation, ordinary least squares, and interpretations of slopes and intercepts of a regression line. Familiarity with functional programming in R and/or Python and ability to define new functions. Familiarity with one or more methods used in machine learning/statistics such as hidden Markov models, CART, neural networks, and/or graphical models. Familiarity with python allowing students to understand simple python scripts. Familiarity with random effects models and ability to implement them in R. Familiarity with the assumptions of regression and methods for investigating the assumptions using R. Familiarity with the use of matrices to model transitions in a biological system with discrete categories.

Prerequisites: Introductory calculus and introductory undergraduate statistics recommended

Credit Restrictions: Students will receive no credit for INTEGBI C201 after completing INTEGBI 201. A deficient grade in INTEGBI C201 may be removed by taking INTEGBI 201, or INTEGBI 201.

Fall and/or spring: 15 weeks - 3 hours of lecture and 3 hours of laboratory per week

Additional Format: Three hours of lecture and three hours of laboratory per week.

Formerly known as: Integrative Biology 201

Also listed as: INTEGBI C201

Introduction to Quantitative Methods In Biology: Read Less [-]

CMPBIO C231 Introduction to Computational Molecular and Cell Biology 4 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022, Fall 2021, Fall 2020 This class teaches basic bioinformatics and computational biology, with an emphasis on alignment, phylogeny, and ontologies. Supporting foundational topics are also reviewed with an emphasis on bioinformatics topics, including basic molecular biology, probability theory, and information theory. Introduction to Computational Molecular and Cell Biology: Read More [+]

Prerequisites: BIO ENG 11 or BIOLOGY 1A (may be taken concurrently); and a programming course ( ENGIN 7 or COMPSCI 61A )

Credit Restrictions: Students will receive no credit for BIO ENG C231 after completing BIO ENG 231 . A deficient grade in BIO ENG C231 may be removed by taking BIO ENG 231 , or BIO ENG 231 .

Instructor: Holmes

Also listed as: BIO ENG C231

Introduction to Computational Molecular and Cell Biology: Read Less [-]

CMPBIO C249 Computational Functional Genomics 4 Units

Terms offered: Fall 2024, Fall 2023 This course provides a survey of the computational analysis of genomic data, introducing the material through lectures on biological concepts and computational methods, presentations of primary literature, and practical bioinformatics exercises. The emphasis is on measuring the output of the genome and its regulation. Topics include modern computational and statistical methods for analyzing data from genomics experiments: high-throughput RNA sequencing data , single-cell data, and other genome-scale measurements of biological processes. Students will perform original analyses with Python and command-line tools. Computational Functional Genomics: Read More [+]

Course Objectives: This course aims to equip students with practical proficiency in bioinformatics analysis of genomic data, as well as understanding of the biological, statistical, and computational underpinnings of this field.

Student Learning Outcomes: Students completing this course should have stronger programming skills, practical proficiency with essential bioinformatics methods that are applicable to genomics research, understanding of the statistics underlying these methods, and awareness of key aspects of genome function and challenges in the field of genomics.

Prerequisites: Math 54 or EECS 16A /B; CS 61A or another course in python; BioE 11 or Bio 1a; and BioE 131. Introductory statistics or data science is recommended

Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week

Additional Format: Three hours of lecture and one hour of discussion per week.

Instructor: Lareau

Also listed as: BIO ENG C249

Computational Functional Genomics: Read Less [-]

CMPBIO C256 Human Genome, Environment and Public Health 4 Units

Terms offered: Spring 2024, Spring 2023, Fall 2020 This introductory course will cover basic principles of human/population genetics and molecular biology relevant to molecular and genetic epidemiology. The latest methods for genome-wide association studies and other approaches to identify genetic variants and environmental risk factors important to disease and health will be presented. The application of biomarkers to define exposures and outcomes will be explored. Recent developments in genomics , epigenomics and other ‘omics’ will be included. Computer and wet laboratory work will provide hands-on experience. Human Genome, Environment and Public Health: Read More [+]

Prerequisites: Introductory level biology/genetics course, or consent of instructor. Introductory biostatistics and epidemiology courses strongly recommended

Credit Restrictions: Students will receive no credit for PB HLTH C256 after completing CMPBIO 156 . A deficient grade in PB HLTH C256 may be removed by taking CMPBIO 156 .

Fall and/or spring: 15 weeks - 2 hours of lecture and 2 hours of laboratory per week

Additional Format: Two hours of lecture and two hours of laboratory per week.

Instructors: Barcellos, Holland

Also listed as: PB HLTH C256

Human Genome, Environment and Public Health: Read Less [-]

CMPBIO C256A Human Genome, Environment and Human Health 3 Units

Terms offered: Spring 2017 This introductory course will cover basic principles of human/population genetics and molecular biology relevant to understanding how data from the human genome are being used to study disease and other health outcomes. The latest designs and methods for genome-wide association studies and other approaches to identify genetic variants, environmental risk factors and the combined effects of gene and environment important to disease and health will be presented. The application of biomarkers to define exposures and outcomes will be explored. The course will cover recent developments in genomics, epigenomics and other ‘omics’, including applications of the latest sequencing technology and characterization of the human microbiome. Human Genome, Environment and Human Health: Read More [+]

Prerequisites: Introductory level biology course. Completion of introductory biostatistics and epidemiology courses strongly recommended and may be taken concurrently

Fall and/or spring: 15 weeks - 3 hours of lecture per week

Additional Format: Three hours of lecture per week.

Also listed as: PB HLTH C256A

Human Genome, Environment and Human Health: Read Less [-]

CMPBIO C256B Genetic Analysis Method 3 Units

Terms offered: Prior to 2007 This introductory course will provide hands-on experience with modern wet laboratory techniques and computer analysis tools for studies in molecular and genetic epidemiology and other areas of genomics in human health. Students will also participate in critical review of journal articles. Students are expected to understand basic principles of human/population genetics and molecular biology, latest designs and methods for genome-wide association studies and other approaches to identify genetic variants, environmental risk factors and the combined effects of gene and environment important to human health. Students will learn how to perform DNA extraction, polymerase chain reaction and methods for genotyping, sequencing, and cytogenetics. Genetic Analysis Method: Read More [+]

Prerequisites: Introductory level biology course. Completion of introductory biostatistics and epidemiology courses strongly recommended and may be taken concurrently with permission. PH256A is a requirement for PH256B; they can be taken concurrently

Fall and/or spring: 15 weeks - 2-2 hours of lecture and 1-3 hours of laboratory per week

Additional Format: Two hours of lecture and one to three hours of laboratory per week.

Also listed as: PB HLTH C256B

Genetic Analysis Method: Read Less [-]

CMPBIO 275 Computational Biology Seminar/Journal Club 1 Unit

Terms offered: Fall 2024, Spring 2024, Fall 2023 This seminar course will cover a wide range of topics in the field of computational biology. The main goals of the course are to expose students to cutting edge research in the field and to prepare students for engaging in academic discourse with seminar speakers - who are often leaders in their fields. A selected number of class meetings will be devoted to the review of scientific papers published by upcoming seminar speakers and the other class meetings will be devoted to discussing other related articles in the field. The seminar will expose students to both the breadth and highest standards of current computational biology research. Computational Biology Seminar/Journal Club: Read More [+]

Repeat rules: Course may be repeated for credit without restriction.

Fall and/or spring: 15 weeks - 1 hour of seminar per week

Additional Format: One hour of seminar per week.

Grading: Offered for satisfactory/unsatisfactory grade only.

Computational Biology Seminar/Journal Club: Read Less [-]

CMPBIO 276 Algorithms for Computational Biology 4 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course will provide familiarity with algorithms and probabilistic models that arise in various computational biology applications, such as suffix trees, suffix arrays, pattern matching, repeat finding, sequence alignment, phylogenetics, hidden Markov models, gene finding, motif finding, linear/logistic regression, random forests, convolutional neural networks, genome-wide association studies, pathogenicity prediction, and sequence-to-epigenome prediction. Algorithms for Computational Biology: Read More [+]

Prerequisites: CompSci 70 AND CompSci 170, MATH 54 OR EECS 16A OR an equivalent linear algebra course

Repeat rules: Course may be repeated for credit with instructor consent.

Instructors: Song, Ioannidis

Algorithms for Computational Biology: Read Less [-]

CMPBIO 290 Special Topics - Computational Biology 1 - 4 Units

Terms offered: Fall 2022, Fall 2021, Spring 2018 This graduate-level course will cover various special topics in computational biology and the theme will vary from semester to semester. The course will focus on computational methodology, but also cover relevant biological applications. This course will be offered according to student demand and faculty availability. Special Topics - Computational Biology: Read More [+]

Prerequisites: Graduate standing in EECS, MCB, Computational Biology or related fields; or consent of the instructor

Fall and/or spring: 15 weeks - 1-3 hours of lecture per week

Additional Format: One to three hours of lecture per week for standard offering. In some instances, condensed special topics classes running from 2-10 weeks may also be offered usually to accommodate guest instructors. Total works hours will remain the same but more work in a given week will be required.

Special Topics - Computational Biology: Read Less [-]

CMPBIO 293 Doctoral Seminar in Computational Biology 2 Units

Terms offered: Fall 2024, Fall 2023, Spring 2023 This interactive seminar builds skills, knowledge and community in computational biology for first year PhD and second year Designated Emphasis students. Topics covered include concepts in human genetics/genomics, microbiome data analysis, laboratory methodologies and data sources for computational biology, workshops/instruction on use of various bioinformatics tools, critical review of current research studies and computational methods, preparation for success in the PhD program and career development. Faculty members of the graduate program in computational biology and scientists from other institutions will participate. Topics will vary each semester. Doctoral Seminar in Computational Biology: Read More [+]

Fall and/or spring: 15 weeks - 2 hours of seminar per week

Additional Format: Two hours of seminar per week.

Doctoral Seminar in Computational Biology: Read Less [-]

CMPBIO C293 Doctoral Seminar in Computational Biology 2 Units

Terms offered: Spring 2024, Fall 2022, Fall 2021 This interactive seminar builds skills, knowledge and community in computational biology for first year PhD and second year Designated Emphasis students. Topics covered include concepts in human genetics/genomics, microbiome data analysis, laboratory methodologies and data sources for computational biology, workshops/instruction on use of various bioinformatics tools, critical review of current research studies and computational methods, preparation for success in the PhD program and career development. Faculty members of the graduate program in computational biology and scientists from other institutions will participate. Topics will vary each semester. Doctoral Seminar in Computational Biology: Read More [+]

Instructors: Moorjani, Rokhsar

Also listed as: MCELLBI C296

CMPBIO 294A Introduction to Research in Computational Biology 2 - 12 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 Closely supervised experimental or computational work under the direction of an individual faculty member; an introduction to methods and research approaches in particular areas of computational biology. Introduction to Research in Computational Biology: Read More [+]

Prerequisites: Standing as a Computational Biology graduate student

Fall and/or spring: 15 weeks - 2-20 hours of laboratory per week

Additional Format: Two to Twenty hours of Laboratory per week for 15 weeks.

Introduction to Research in Computational Biology: Read Less [-]

CMPBIO 294B Introduction to Research in Computational Biology 2 - 12 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 Closely supervised experimental or computational work under the direction of an individual faculty member; an introduction to methods and research approaches in particular areas of computational biology. Introduction to Research in Computational Biology: Read More [+]

CMPBIO 295 Individual Research for Doctoral Students 1 - 12 Units

Terms offered: Summer 2024 10 Week Session, Summer 2023 10 Week Session, Summer 2022 10 Week Session Laboratory research, conferences. Individual research under the supervision of a faculty member. Individual Research for Doctoral Students: Read More [+]

Prerequisites: Acceptance in the Computational Biology PhD program; consent of instructor

Fall and/or spring: 15 weeks - 1-20 hours of laboratory per week

Summer: 10 weeks - 1.5-30 hours of laboratory per week

Additional Format: One to twenty hours of laboratory per week. One and one-half to thirty hours of laboratory per week for 10 weeks.

Individual Research for Doctoral Students: Read Less [-]

CMPBIO 477 Introduction to Programming for Bioinformatics Bootcamp 1.5 Unit

Terms offered: Prior to 2007 The goals of this course are to introduce students to Python, a simple and powerful programming language that is used for many applications, and to expose them to the practical bioinformatic utility of Python and programming in general. The course will allow students to apply programming to the problems that they face in the lab and to leave this course with a sufficiently generalized knowledge of programming (and the confidence to read the manuals) that they will be able to apply their skills to whatever projects they happen to be working on. Introduction to Programming for Bioinformatics Bootcamp: Read More [+]

Prerequisites: This is a graduate course and upper level undergraduate students can only enroll with the consent of the instructor

Summer: 3 weeks - 40-40 hours of workshop per week

Additional Format: Organized as a bootcamp, the ten-day course will include two sessions daily, each consisting of roughly two hours of lecture and up to three hours of hands on exercises.

Subject/Course Level: Computational Biology/Other professional

Introduction to Programming for Bioinformatics Bootcamp: Read Less [-]

Contact Information

Computational biology graduate group.

574 Stanley Hall

Phone: 510-642-0379

Fax: 510-666-3399

[email protected]

Director, CCB

Elizabeth Purdom

[email protected]

Executive Director, CCB

Phone: 510-666-3342

[email protected]

Graduate Program Manager

574 Stanley Hall, MC #3220

[email protected]

Head Graduate Advisor and Chair for the PhD & DE

John Huelsenbeck

[email protected]

CCB DE Advising

[email protected]

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The field of computational and systems biology represents a synthesis of ideas and approaches from the life sciences, physical sciences, computer science, and engineering. Recent advances in biology, including the human genome project and massively parallel approaches to probing biological samples, have created new opportunities to understand biological problems from a systems perspective. Systems modeling and design are well established in engineering disciplines but are newer in biology. Advances in computational and systems biology require multidisciplinary teams with skill in applying principles and tools from engineering and computer science to solve problems in biology and medicine. To provide education in this emerging field, the Computational and Systems Biology (CSB) program integrates MIT's world-renowned disciplines in biology, engineering, mathematics, and computer science. Graduates of the program are uniquely prepared to make novel discoveries, develop new methods, and establish new paradigms. They are also well-positioned to assume critical leadership roles in both academia and industry, where this field is becoming increasingly important.

Computational and systems biology, as practiced at MIT, is organized around "the 3 Ds" of description, distillation, and design. In many research programs, systematic data collection is used to create detailed molecular- or cellular-level descriptions of a system in one or more defined states. Given the complexity of biological systems and the number of interacting components and parameters, system modeling is often conducted with the aim of distilling the essential or most important subsystems, components, and parameters, and of obtaining simplified models that retain the ability to accurately predict system behavior under a wide range of conditions. Distillation of the system can increase the interpretability of the models in relation to evolutionary and engineering principles such as robustness, modularity, and evolvability. The resulting models may also serve to facilitate rational design of perturbations to test understanding of the system or to change system behavior (e.g., for therapeutic intervention), as well as efforts to design related systems or systems composed of similar biological components.

More than 70 faculty members at the Institute participate in MIT's Computational and Systems Biology Initiative (CSBi). These investigators span nearly all departments in the School of Science and the School of Engineering, providing CSB students the opportunity to pursue thesis research in a wide variety of different MIT laboratories. It is also possible for students to arrange collaborative thesis projects with joint supervision by faculty members with different areas of expertise. Areas of active research include behavioral genetics and genomics; bioengineering and neuroengineering; biological networks and machine learning; cancer systems biology; cellular biophysics; chemical biology and metabolomics; evolutionary and computational biology; microbiology and systems ecology; molecular biophysics and structural biology; precision medicine and medical genomics; quantitative imaging; regulatory genomics, epigenomics, and proteomics; single cell manipulations and measurement; stem cell and developmental systems biology; synthetic biology and biological design; and systems immunology.

The CSB PhD program is an Institute-wide program that has been jointly developed by the Departments of Biology, Biological Engineering, and Electrical Engineering and Computer Science. The program integrates biology, engineering, and computation to address complex problems in biological systems, and CSB PhD students have the opportunity to work with CSBi faculty from across the Institute. The curriculum has a strong emphasis on foundational material to encourage students to become creators of future tools and technologies, rather than merely practitioners of current approaches. Applicants must have an undergraduate degree in biology (or a related field), bioinformatics, chemistry, computer science, mathematics, statistics, physics, or an engineering discipline, with dual-emphasis degrees encouraged.

All students pursue a core curriculum that includes classes in biology and computational biology, along with a class in computational and systems biology based on the scientific literature. Advanced electives in science and engineering enhance both the breadth and depth of each student's education. During their first year, in addition to coursework, students carry out rotations in multiple research groups to gain a broader exposure to work at the frontier of this field, and to identify a suitable laboratory in which to conduct thesis research. CSB students also serve as teaching assistants during one semester in the second year to further develop their teaching and communication skills and facilitate their interactions across disciplines. Students also participate in training in the responsible conduct of research to prepare them for the complexities and demands of modern scientific research. The total length of the program, including classwork, qualifying examinations, thesis research, and preparation of the thesis is roughly five years.

The CSB curriculum has two components. The first is a core that provides foundational knowledge of both biology and computational biology. The second is a customized program of electives that is selected by each student in consultation with members of the CSB graduate committee. The goal is to allow students broad latitude in defining their individual area of interest, while at the same time providing oversight and guidance to ensure that training is rigorous and thorough.

Core Curriculum

The core curriculum consists of three classroom subjects plus a set of three research rotations in different research groups. The classroom subjects are comprised of modern biology, computational biology, and a literature-based exploration of current research frontiers and paradigms, which is required of all first-year students in the program . Students also participate in three research rotations of one to two months' duration during their first year to expose them to a range of research activities in computation and systems biology, and to assist them in choosing a lab. Students are encouraged to gain experience in experimental and computational approaches taken across different disciplines at MIT.

Advanced Electives

To develop breadth and depth, add to the base of the diversified core, and contribute strength in areas related to their interest and research direction, students must take four advanced electives. Each student designs a program of advanced electives that satisfies the distribution and area requirements in close consultation with members of the graduate committee.

Additional Subjects

CSB PhD students may take classes beyond the required diversified core and advanced electives described above. These additional subjects can be used to add breadth or depth to the proposed curriculum, and might be useful to explore advanced topics relevant to the student's thesis research in later years. The CSB Graduate Committee works with each graduate student to develop a path through the curriculum appropriate for his or her background and research interests.

Training in the Responsible Conduct of Research

Throughout the program, students will be expected to attend workshops and other activities that provide training in the ethical conduct of research. This is particularly important in interdisciplinary fields such as computational and systems biology, where different disciplines often have very different philosophies and conventions. By the end of the fifth year, students will have had about 16 hours of training in the responsible conduct of research.

Qualifying Exams

In addition to coursework and a research thesis, each student must pass a written and an oral qualifying examination at the end of the second year or the beginning of the third year. The written examination involves preparing a research proposal based on the student's thesis research, and presenting the proposal to the examination committee. This process provides a strong foundation for the thesis research, incorporating new research ideas and refinement of the scope of the research project. The oral examination is based on the coursework taken and on related published literature. The qualifying exams are designed to develop and demonstrate depth in a selected area (the area of the thesis research) as well as breadth of knowledge across the field of computational and systems biology.

Thesis Research

Research will be performed under the supervision of a CSBi faculty member, culminating in the submission of a written thesis and its oral defense before the community and thesis defense committee. By the second year, a student will have formed a thesis advisory committee that they will meet with on an annual basis.

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• Prospective Students
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• Degree Programs

Computational Biology PhD Programs

The Computational Biology Program offers a PhD degree in Computational Biology. The graduate program, one of the top in the U.S. in Bioinformatics and Computational Biology, involves faculty who are recognized leaders in the fields of structure prediction of proteins and protein complexes, molecular simulation, systems biology, genomics, protein design, and drug discovery. The program faculty and students actively engage in international community-wide activities in bioinformatics and computational biology. For more information, see Computational Biology Program /  The Center for Computational Biology . The University of Kansas has world-class credentials in life sciences and information technology. The program complements on-going efforts to expand these areas of research and education at  The University of Kansas .

If you have any questions regarding the PhD program, contact Program Director Dr. Ilya Vakser at  [email protected] .

Computational Biology

Our interdisciplinary M.S. in Computational Biology program is designed to provide students with expertise in the leading quantitative methods underlying modern biomedical science. The program is an in-depth response to the ever-growing need for computational methods and mathematical models in processing, analyzing, and interpreting the vast amounts of biological data generated by high-throughput techniques. Computer simulations are required to understand and predict the dynamics of complex biological systems. Precision medicine, drug development, and cancer research are only a few among the many thriving fields increasingly relying on quantitative genomics, bioinformatics, and systems biology.

The M.S. in Computational Biology (MS-CB) presents a unique, rigorous training program, equipping students with theoretical understanding and practical mastery of state-of-the-art applications of computational approaches in biology and medicine. Our faculty from Weill Cornell Medicine, Sloan-Kettering Institute, and Cornell Tech are world-class leaders in computational biology research and applications.

Upon graduation, with extensive training and field-specific, curricular workshops in career development, students will be prepared to launch successful professional careers at the forefront of data analytics, bioinformatics, and computer modeling, for example in the pharmaceutical or biotech industries. Likewise, for those interested in pursuing further education in computational biology at the PhD level, this degree will attest to their preparation and enhance their competitiveness.

Our  curriculum  is highly interdisciplinary and includes training in cutting-edge bioinformatics, statistics, machine learning, computation and simulation, quantitative biology, and genomics. The training emphasizes hands-on computer labs and practical skills to prepare students for careers beyond the classroom.

Program features include:

• 18 months duration, full-time study
• cohesive interdisciplinary educational program
• individual mentored research project
• career development training

Please  see here  for a complete list of faculty

Tuition, Fees and Scholarships

Please refer to the  student services website  for program-specific details on tuition and fees. Please note that this tuition cost and fees are set for the current academic year and are subject to change.

A small number of partial scholarships are available. Applicants applying by the priority deadline are automatically considered for these merit-based scholarships.

Program Requirements

Applicants must hold a bachelor’s degree in science or engineering. Applicants must have completed undergraduate level coursework in calculus, linear algebra, probability theory or statistics, and computer programming.

We seek applications from students with diverse undergraduate degrees and welcome applications from talented individuals of all backgrounds. 

All application forms and supporting documents can be  submitted online . You will be asked to submit or upload:

• Personal Statement describing your background and specific interest in the MS-CB program.
• Résumé/C.V.
• Three letters of recommendation. Letters must be submitted electronically as instructed through the online application.
• Transcripts from all previously attended colleges and universities
• Domestic Transcripts - Unofficial transcripts from U.S. institutions may be submitted for application review. Official transcripts will be requested from accepted students prior to matriculation.
• If using WES, please select the WES Basic Course-by-Course evaluation and choose "Cornell University - Manhattan NY" as the recipient with "Weill Graduate School of Medical Sciences" as the School/Division 
• Evaluations are accepted only from  current members of the National Association of Credit Evaluation Services (NACES) . Official course-by-course evaluations are required for application review.
• $80 application fee
• Results of the General Graduate Record (GRE) examination are  optional . The Institution Code Number is 2119.
• Scores from the  Test of English as a Foreign Language (TOEFL) ,  International English Language Testing System (IELTS) , or  Duolingo English Test . Test scores are valid for two years after the test date. To see if you qualify for an exemption, see below.
• To submit your official TOEFL scores, please go to  http://www.ets.org/toefl  and request your scores to be sent to Weill Cornell Graduate School using code 2119. Please monitor your application to ensure that your scores are populated by ETS.  
• IELTS results must be submitted directly via e-delivery to “Weill Cornell Graduate School of Medical Sciences.”
• Results for the Duolingo English Test, applicants must submit their results directly through Duolingo to “Weill Cornell Graduate School of Medical Sciences".

Application Timeline & Deadlines

The application site for Fall 2024 admission is open. 

We are still accepting applications for the Fall 2024 class. We are operating with a rolling admissions process at this point and encourage you to submit your application as early as possible to avoid potential seat capacity or timing restrictions.  

Final deadline for applications: May 1, 2024. 

English Language Proficiency Exam Exemptions

The English language proficiency requirement may be waived if an applicant meets at least one of the following criteria:

• Citizenship/Permanent Residency
• If the applicant is a citizen or permanent resident of the United States or its territories (e.g., Puerto Rico), or a citizen of the United Kingdom, Ireland, Australia, New Zealand, or Canada, they are exempt.
• Applicants who are citizens of all other countries, including India, Pakistan, the Philippines, Hong Kong, Singapore, etc. are not exempt and must submit English language proficiency exam scores.
• English-Language Instruction
• Applicants who, at the time of enrollment, have studied in full-time status for at least two academic years within the last  five  years in the United States, the United Kingdom, Ireland, Australia, or New Zealand, or with English language instruction in Canada or South Africa, are exempt.
• Applicants must submit a transcript that shows they studied in one of the approved locations, and that the academic program was at least two years in length.
• Even if English was the language of instruction of the course or institution, it must have been in one of the eligible locations, otherwise the applicant is not exempt from the requirement.

Prospective Student Events

We're always working on putting events together. Be sure to check back soon for more event listings.

Faculty Stories

• Aguiar-Pulido, Vanessa
• Bao, Zhirong
• Bendall, Matthew
• Berger, Michael
• Betel, Doron
• Brady, Nicholas
• Christini, David
• Davis, Melissa
• Dundar, Friederike
• Elemento, Olivier
• Hajirasouliha, Iman
• Imielinski, Marcin
• Kentsis, Alex
• Khurana, Ekta
• Krogh-Madsen, Trine
• Krumsiek, Jan
• Landau, Dan
• Laughney, Ashley
• Lee, Guinevere
• Leslie, Christina
• Mason, Christopher
• Nixon, Douglas
• Papaemmanuil, Elli
• Sboner, Andrea
• Schultz, Nikolaus
• Skrabanek, Luce
• Tilgner, Hagen
• Ventura, Andrea

Courses and Required Curricular Components

• Analysis of Next-Generation Sequencing Data
• Career Development in Computational Biology
• Cellular and Molecular Biology
• Computational Biology Research
• Data Structures and Algorithms for Computational Biology
• Dynamic Models in Biology
• Functional Interpretation of High-Throughput Data
• MS-CB Thesis Research
• MS-CB Thesis Research Exploration 1&2
• Quantitative Genomics and Genetics

Student Stories

I have enjoyed exploring a bunch of different areas of research, specifically those to which I was completely new. Everyone here has been extremely supportive and there has been a lot of room for growth. Overall it's been really fun figuring out what I'd like to do moving forward!

Weill Cornell is unique in how focused it is on medical science research. There is no other institution where I can so easily find professors to collaborate with for clinical research. In the short time I have spent in the program, I have meaningfully contributed to several projects that will be published.

Student Handbook

To view the MSCB Student Handbook, click here .

  Contact Information

  Trine Krogh-Madsen, PhD, Director 413 E. 69th St, Box 190 New York, NY 10065 (646) 962 - 5392 [email protected]

Lucia Li , Program Coordinator 1300 York Ave, Box 65 New York, NY 10065 [email protected]

Weill Cornell Medicine Graduate School of Medical Sciences 1300 York Ave. Box 65 New York, NY 10065 Phone: (212) 746-6565 Fax: (212) 746-8906

PhD in Bioinformatics & Computational Biology

WPI’s PhD in Bioinformatics and Computational Biology (BCB) will prepare you to become a new type of scientist who can model complex biological processes and analyze and interpret the staggering volume of biological data arising from endeavors such as the Human Genome Project.

Value Proposition Description

Our bioinformatics PhD program is truly interdisciplinary, enabling you to develop expertise across three key fields of study: Biology, Computer Science, and Mathematics. You will become well versed in all three as you work alongside our expert faculty researchers to create and apply the tools and algorithms necessary to predict, prevent, and cure disease, and to solve pressing environmental problems.

In our PhD in bioinformatics, you will work closely with a faculty advisor to plan an interdisciplinary course of study and research tailored to your background and interests. Through core courses, you will achieve a strong foundation in Biology, Computer Science, and Mathematics. Our bioinformatics and computational biology PhD also enables students to study advanced topics, including biovisualization, biomedical database mining, simulation in biology, and statistical methods in genetics and bioinformatics.

With our bioinformatics PhD program, you will gain career-boosting experiences through a required teaching and mentoring component, professional skills seminar, and optional internship with an industry partner.

Our bioinformatics PhD students are immersed in ground-breaking research aimed at developing and utilizing quantitative techniques to tackle important biological problems, from understanding the causes of complex diseases to modeling pollinator-plant relationships in ecosystems.

You’ll have many opportunities to get involved in such cutting-edge research in collaboration with faculty and students from departments across campus. In the first year of your program, you will complete at least two research rotations before choosing a research advisor.

Students in WPI’s bioinformatics program learn cutting-edge approaches in areas such as artificial intelligence (AI) and machine learning, next-generation sequencing, bioinformatics, systems biology, high-performance computing, big data mining, and visualization.

In addition to wet labs and facilities at UMMS, students may access resources in WPI’s Visualization Laboratory, Knowledge Discovery and Data Mining Laboratory, Database Systems Laboratory, and in several powerful computer clusters.

Students apply varied approaches to understand genetic and infectious diseases, prevent ecological disasters, develop new drugs and computational diagnostics tools, and explore new biological phenomena.

Biology, computer science, and mathematics—these disciplines contribute to advances in biological and biomedical science. At WPI, collaboration between disciplines leads to greater discoveries.

You’ll work alongside faculty and student researchers from across multiple disciplines in our state-of-the-art Life Sciences and Bioengineering Center at Gateway Park, where an open-plan lab format encourages collaboration. You will also have access to computational labs, including our groundbreaking Visualization and Image Science Laboratory.

Need to Earn a Bioinformatics Masters?

Maybe you already have a solid foundation in computing and biology, but are looking to become a bioinformatics scientist in one of the top bioinformatics PhD programs? Do you want to leverage cutting-edge approaches in the lab to your workplace and discover a high ROI with a bioinformatics PhD salary? Our bioinformatics masters is unlike many others as it draws from biology, computer science, and mathematics for a truly interdisciplinary experience. A master’s in bioinformatics will give you the expertise to solve real-world problems worldwide and in healthcare.

Have a Passion for Biological Systems? Focus Your College Search & Explore a BS in Bioinformatics.

Have you always had an edge for mathematics, computers, and biology? With our bioinformatics bachelor’s degree , you don’t have to choose between the three. Unlike many schools that offer this degree as a concentration within biology, our bioinformatics undergraduate program encompasses all three disciplines. Whether you’re interested in statistical methods in genetics or database mining, our BS enables you to explore what interests you most. Looking to save some time? We offer a combined BS/MS option in five short years!

Maybe you have an interest in learning how to apply math and computer science to biological issues, but want to focus on a different discipline for your major? We offer a flexible minor in bioinformatics which provides students the preparedness necessary for a career that requires some critical thinking in quantitative biology.

Refer a Friend

Do you have a friend, colleague, or family member who might be interested in Worcester Polytechnic Institute’s (WPI) graduate programs? Click below to tell them about our programs.

Faculty Profiles

My research is interdisciplinary and spans the fields of bioinformatics of complex diseases, computational genomics, systems biology, and biomedical data analytics. We bring expertise in machine learning, data mining, and massive data analytics to study molecular mechanisms underlying genetic disorders, such as cancer, diabetes, and autism, and deadly infections, such as pandemic flu. Our approaches benefit from integrating multi-omic, systems, and structural biology data.

I have a long-standing interest in applying computer science and mathematics to solve biological problems. I am currently the Associate Director of WPI’s Program in Bioinformatics and Computational Biology, and I am always looking for students with interests in this exciting interdisciplinary area. One of my goals in teaching biology is to help students to think more quantitatively about biological questions. A few years ago, my colleague Dr. Brian White of UMass Boston and I were awarded a grant from the NSF to develop a course, “Simulation in Biology”.

Work in my lab is focused on defining the cellular mechanisms that maintain genome stability in normal cells and understanding how these pathways are corrupted in cancer cells.

Carolina Ruiz is the Associate Dean of Arts and Sciences and the Harold L. Jurist ’61 and Heather E. Jurist Dean's Professor of Computer Science. She joined the WPI faculty in 1997. Prof. Ruiz’s research is in Artificial Intelligence, Machine Learning, and Data Mining, and their applications to Medicine and Health. She has worked on several clinical domains including sleep, stroke, obesity and pancreatic cancer. Prof.

I have a passion for understanding how living systems work, as well as for sharing my love of biology and research with the next generation of scientists and informed citizens.

The central goal of my lab is to understand the regulatory mechanisms that underlie mycobacterial stress tolerance. We combine genetics, genomics, transcriptomics and biochemistry to understand how mycobacteria respond to, and ultimately survive, stressful conditions.

Professor Wu's research interest lies in applying the power of statistical science to promote biomedical researches. In statistical genetics, he is developing novel statistical theory and methodology to analyze genome-wide association (GWA) data and deep (re)sequencing data to hunt new genetic factors for complex human diseases. In epigenetics, he is studying gene expression regulation mechanisms through chromatin interaction, and RNA silencing pathways in the developmental stages of germ-line cells.

WPI is proud to be the recipient of not one, but two National Science Foundation Research Traineeship programs. The programs provide exceptionally talented graduate students with specialized training and funding assistance to join careers at the forefront of technology and innovation. The programs are for graduate students in research-based master's and doctoral degree programs in STEM. Learn more .

PhD in Bioinformatics Data Science

A Ph.D. in Bioinformatics Data Science will train the next-generation of researchers and professionals who will play a key role in multi- and interdisciplinary teams, bridging life sciences and computational sciences. Students will receive training in experimental, computational and mathematical disciplines through their coursework and research. Students who complete this degree will be able to generate and analyze experimental data for biomedical research as well as develop physical or computational models of the molecular components that drive the behavior of the biological system.

Students must complete a minimum of 15 hours of coursework, plus 3 credit hours of seminar, 6 credit hours of research and 9 credit hours of doctoral dissertation. The Ph.D. requires a minimum of 33 credits. Students who are admitted directly after a B.S. degree will be required to complete up to 9 additional credits in order to fulfill the core curriculum in the following areas: Database Systems, Statistics, and Introduction to Discipline. In addition, if students entering the program with an M.S. degree are lacking equivalent prerequisites, they also will be required to complete courses in these three areas; however, these courses may fulfill the elective requirement in the Ph.D. program, if approved in the program of study.

Academic Load

PhD students holding research assistantships (or teaching) are considered full-time with 6 credit hours . Students without RA or TA  are considered full-time if enrolled in at least 9 credit hours or in sustaining credit. Those enrolled for fewer than 9 credit hours are considered part-time students. Generally, a maximum load is 12 graduate credit hours; however, additional credit hours may be taken with the approval of the student’s adviser and the Graduate College. A maximum course load in either summer or winter session is 7 credit hours. Permission must be obtained from the Graduate College to carry an overload in any session. 

Bioinformatics Data Science Courses

Students must take one course in each of the following areas (9 credits):

Prerequisites

Students must fulfill core curriculum in each of the following areas (3-9 credits):

Elective Courses

Students must take two courses to compliment their bioinformatics data science dissertation project (6 credits): 

See Elective courses

Students must take six semesters of seminar (three 0 credit; three 1 credit) and give a presentation during three semesters.

Other Requirements:

• Formation of Graduate Dissertation Committee
• Successful completion of Graduate Preliminary Exam
• Research on a significant scientific problem
• Successful completion of Ph.D. Candidacy Exam
• Successful completion of Dissertation Defense

Formation of Graduate Committee

The student needs to establish a Dissertation Committee within the first year of study. The Committee should consist of at least four faculty members, including the primary faculty advisor (serving as the Committee Chair), a secondary faculty advisor (in a complementary field to the primary advisor), a second faculty from the home department, and one CBCB affiliate faculty outside the Departments of the primary and secondary advisors or from outside the University. Students must complete the Dissertation Committee Formation form and submit to the Associate Director.

Students should convene their dissertation committee at least once every six months.

Preliminary Examination

The preliminary examination should be taken before the end of the fourth semester and will consist of an oral exam in subjects based on the Bioinformatics Data Science core.* In recognition of the importance of the core curriculum in providing a good test of the student’s knowledge, students must achieve a minimum 3.0 GPA in the core curriculum before taking the preliminary exam. Students will not be permitted to take the preliminary examination if the core grade requirements and cumulative GPA of 3.0 has not been achieved. The exam will be administered by the Preliminary Exam Committee , which will consist of one instructor from each of the three core courses. Each member of the Committee will provide a single grade (pass, conditional pass or fail) and the final grades will be submitted via the Results of Preliminary Exam Form :

• Pass . The student may proceed to the next stage of his/her degree training.
• Conditional pass . In the event that the examination committee feels that the student did not have an adequate background or understanding in one or more specific areas, the Preliminary Exam Committee will communicate the conditional pass to the student and must provide the student with specific requirements and guidelines for completing the conditional pass. The student must inform the Preliminary Exam Committee, the Graduate Program Director and Program Committee when these conditions have been completed. The Preliminary Exam Committee will then meet with the student to ensure all recommendations have been completed and whether a re-examination is necessary. If required, the re-examination will be done using the same format and prior to the beginning of the next academic semester. If the student still does not perform satisfactorily on this re-examination, he/she will then be recommended to the Graduate Affairs Committee for dismissal from the graduate program.
• Failure . This outcome would indicate that the Examination Committee considers the student incapable of completing degree training. The student’s academic progress will be reviewed by the Graduate Affairs Committee, who will make recommendations to the Program Director regarding the student’s enrollment status. The Program Director may recommend to the Graduate College that the student be dismissed from the Program immediately.

*Students who need to complete prerequisite courses may request a deadline extension for the preliminary and subsequently the candidacy examination. Requests must be submitted to the Graduate Program Committee prior to the start of the third semester.

Candidacy Exam

The candidacy examination must be completed by the end of the sixth semester of enrollment.* It requires a formal, detailed proposal be submitted to the Dissertation Committee and an oral defense of the student’s proposed research project. Upon the recommendation of the Dissertation Committee, the student may be admitted to candidacy for the Ph.D. degree. The stipulations for admission to doctoral candidacy are that the student has (i) completed one academic years of full-time graduate study in residence at the University of Delaware, (ii) completed all required courses with the exception of BINF865 and BINF969, (iii) passed the preliminary exams, (iv) demonstrated the ability to perform research, and (v) had a research project accepted by the Dissertation Committee. Within one week of the candidacy exam, complete and submit the Recommendation for Candidacy for Doctoral Degree form for details. A copy of the completed form should be given to the Associate Director.

*Students who need to complete prerequisite courses may request a deadline extension for the preliminary and subsequently the candidacy examination.  Requests must be submitted to the Graduate Program Committee prior to the start of the third semester.

Dissertation Exam

The dissertation examination of the Ph.D. program will involve the approval of the written dissertation and an oral defense of the candidate’s dissertation.  The written dissertation will be submitted to the Dissertation Committee and the CBCB office at least three weeks in advance of the oral defense date.  The oral defense date will be publicly announced at least two weeks prior to the scheduled date. The oral presentation will be open to the public and all members of the Bioinformatics Data Science program. The Dissertation Committee will approve the candidate’s dissertation. The student and the primary faculty advisor will be responsible for making all corrections to the dissertation document and for meeting all Graduate College deadlines.  Within one week of the dissertation defense, complete and submit the Certification of Doctoral Dissertation Defense Form. A copy of the completed form should be given to the Associate Director.

Applied Mathematics

Ph.d. program in computational biology.

M.S. in Computational Biology

A Joint Computational Biology Department and Department of Biological Sciences   Program

MSCB mission statement

The MSCB program seeks to train the world’s best Computational Biologists at the Master’s level. The curriculum provides both breadth and depth of training in Computational Biology and is built on a solid foundation of Biology, Computer Science, Statistics, and Machine Learning (Data Sciences). Interested students are also given opportunities to pursue research. Our graduates are prepared for rewarding jobs in industry or to pursue their doctoral degrees at top universities.

Bioinformatics.  Personalized medicine. Sequenced microbial genomes. Progress in gene therapy. Improvements in nutrition.

Making sense of these advances in biomedical science and of the knowledge explosion in domains such as genetics, drug design, neuroscience, and environmental health requires both a sophisticated understanding of biological questions and powerful analytical tools to solve them. The integrated discipline of computational biology/bioinformatics represents the application of modern computer science, statistics, and mathematics to exploring biological and biomedical problems. The Department of Biological Sciences in the Mellon College of Science and the Ray and Stephanie Lane Computational Biology Department in the School of Computer Science combine their world-class strengths in computer science and biology with the strong tradition of interdisciplinary research at Carnegie Mellon into a unique training program in this emerging field.

Coursework consists of Foundation Courses, Background Courses, and Breadth & Depth Courses in a wide array of disciplines such as computer science, machine learning, math, statistics, biology, chemistry, biomedical engineering, and information management. Students have the option of conducting in-depth research in addition to coursework, and are also encouraged to seek external internships after their first year. Students pursue this degree full-time and complete the program in 3-4 semesters.

Students who have completed the program have gone on to work in a wide range of industries in biotech and pharma as well as goverment and academic institutions. Recent graduates have been employed at companies and institutes such as the J. Craig Venter Institute, Thermo Fisher Scientific, Philips Research, and Broad Institute of MIT and Harvard, to name a few. Other graduates have gone on to pursue Ph.D. degrees at a number of top universities around the world.

How to Apply

The CMU Rales Fellow Program is dedicated to developing a diverse community of STEM leaders from underrepresented and underresourced backgrounds by eliminating cost as a barrier to education. Learn more about this program for master's and Ph.D. students. Learn more

Computational Biology Twitter

Biological sciences twitter, departments.

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2024 Best Online PhD in Biology [Doctorate Guide]

If you’re interested in the sciences of living things, pursuing your PhD in Biology might be a strategic next step on your educational path.

The biological sciences help us learn more about how our world operates, and this fascinating field has many specialties to choose from. Whether you want to focus on the human body or explore the living world around us, there are many options for you to consider.

Editorial Listing ShortCode:

Let’s take a look at how earning a doctorate degree in biology might further your educational and professional goals.

Universities Offering Online Doctorate in Biology Degree Programs

Methodology: The following school list is in alphabetical order. To be included, a college or university must be regionally accredited and offer degree programs online or in a hybrid format.

George Mason University

George Mason University’s PhD in Bioinformatics and Computational Biology program is available 100% online. Students are required to complete 72 total credits. Class options include Systems Biology, Biological Data Analysis, Biological Sequence and Genome Analysis, Research Ethics, Numerical Methods for Bioinformatics, and more. Courses are delivered synchronously.

George Mason University is accredited by the Southern Association of Colleges and Schools Commission on Colleges.

Nova Southeastern University

Nova Southeastern University offers a PhD in Marine Biology and Oceanography. Applications are accepted on a rolling basis for fall, spring, and summer terms. The degree can be earned on campus or online. Students are usually able to finish within 5 years. Graduates have gone on to careers in the government and academia.

Nova Southeastern University is accredited by the Southern Association of Colleges and Schools Commission on Colleges.

Texas A&M University

Texas A&M University offers a Doctor of Philosophy in Biomedical Sciences. The program includes 4 tracks: Physiology and Developmental Biology, Infection, Immunity, and Epidemiology, Diagnostics and Therapeutics, and Biomedical Genomics and Bioinformatics. Each track can be tailored to specific research interests.

Texas A&M University is accredited by the Southern Association of Colleges and Schools Commission on Colleges.

Texas Tech University

Texas Tech University offers a hybrid program for a Doctor of Philosophy in Curriculum and Instruction (Track in STEM) that requires the completion of 63 credit hours. Much of the coursework is completed online, but in the summer, students take on-campus intensive courses. Prospective students must have a master’s degree to apply.

Texas Tech University is accredited by the Southern Association of Colleges and Schools Commission on Colleges.

University of Florida

The University of Florida offers a PhD in Anatomical Science Education. Students must complete at least 90 credit hours to graduate. Coursework includes Medical Human Embryology, Science Curriculum Development, Medical Histology, Medical Cell Biology, Essential Human Anatomy, and more. Students must also successfully defend a dissertation.

The University of Florida is accredited by the Southern Association of Colleges and Schools Commission on Colleges.

University of Mississippi

The University of Mississippi offers a Doctor of Philosophy in Secondary Education with an emphasis in Biology. This program is intended for students with at least 2 years of professional teaching experience. The full degree is only available at the main campus, but select courses are available online or at regional campuses.

The University of Mississippi is accredited by the Southern Association of Colleges and Schools Commission on Colleges.

PhD in Biology Online Programs

Biology is the study of living things, and there are many specific areas in biology in which doctoral students can concentrate.

Some of these biological concentrations include:

• Cellular and molecular biology
• Ecology and environmental biology
• Evolutionary biology and genomics
• Epidemiology
• Forensic biology

Biological studies can range from the microscopic world of the cell to understanding how our existence can impact our future.

Those who have earned their Ph.D. in Biology are able to examine our world on a very different level to understand the “how” and “why” of life as we know it. Those who earn their doctorate degree in biology may continue their careers in research, analytics, or field work. Many PhD graduates even go on to become educators for the next generation of biology students.

The field of biology is expansive, so you’ll often take a certain number of core classes, electives, and courses that are specific to your concentration. Many schools offer several areas of focus to help you further define your path.

Pursuing a doctorate degree in biology can provide you with an opportunity to hone your research and analytical skills while selecting a focus for your studies and potential career path.

Biology Careers and Salaries

The variety of degree programs in biology can help open the doors to a range of professions in related fields. Your career path will likely depend on your area of concentration, field work, and skill sets, among other factors.

According to the Bureau of Labor Statistics , here are some professions related to the field of biology, along with their median salaries.

Many biology doctoral students focus on scientific research in a variety of specialties. For instance, some may aim to develop cutting-edge medical intervention, while others want to connect with wildlife and our environment on a cellular level.

Students who pursue a PhD in Biology are often encouraged to gain experience in the field as part of their curriculum. This could help you narrow down the field and concentration of your studies and potential career path.

Biology Doctorate Curriculum & Courses

Since there are so many areas of study within a doctorate degree in biology, you’ll often take courses that apply to your specific concentration.

While coursework can vary between PhD programs in biology, here are a few courses you may encounter:

• Evolutionary Ecology : This course allows you to learn more about theories and evidence surrounding the evolutionary process and its impact on various species.
• Understanding Genomics in Medicine : In this course, you’ll get in-depth exposure to the Human Genome Project, and you’ll study how diseases impact us on a genetic level.
• Cell Biology : From macromolecules to microscopy, this course will provide detailed analysis of how cells work.
• Animal Behavior : Animal behavior has a variety of origins, from evolutionary to neurological, and you’ll review evidence for all behavior.
• Biology of Parasites : Parasites and pathogens are common dependent species of living organisms and are the focus of this course.
• Regional Biology : In this course, you’ll examine how environmental factors, such as heat or freezing temperatures, can impact local biology.
• Developmental Genomics : This course examines how genes and molecular interaction impact biological development.
• Analytical Biotechnology : This course combines technology and analytical skills to examine biomolecules and report findings.
• Cell Proliferation : This course studies the processes through which cells divide or multiply.
• Freshwater Biology : In this course, you’ll examine freshwater sources, such as ponds and lakes, to examine the overall ecology and health of biological factors there.

Your courses can also help you develop research skill sets for the dissertation component of your program.

Online PhD in Biology Admissions Requirements

PhD programs in biology can have different admissions requirements. You can visit a school’s website or call their admissions office to verify the specific criteria for their application process.

For many schools, doctoral applicants are asked to provide the following:

• GRE or GMAT scores (only some schools require them)
• Bachelor or masters degree in biology or related field like an online masters in biostatistics
• Official undergraduate and graduate transcripts
• Letters of recommendation
• Statement of intent

As part of the application process, you may also be asked to complete an application, attend interviews with those in the department, and present prior thesis work.

Online Biology PhD Programs Accreditation

When reviewing various schools that offer a doctorate degree in biology, you may wish to only pay attention to institutions that hold regional accreditation. Programs that have earned accreditation have been examined for their educational excellence. This means the courses and instructors have earned a positive reputation for their impact on students.

Qualification for future professional memberships and licenses may be tied to participation in an accredited program. Additionally, many employers indicate that a degree from an accredited school is necessary for employment. This could also impact the publishing of your studies. To verify a school’s accreditation status, you can visit the website of the Council for Higher Education Accreditation (CHEA) .

Financial Aid and Scholarships

If you’re interested in financial assistance for your doctoral degree, there are various options available for students who qualify.

To see if you’re eligible for government assistance, you can complete the Free Application for Federal Student Aid (FAFSA) online. This federal program provides need-based financial aid to students across the country. Student loans are the most common form of federal aid. Additionally, you may wish to check with your prospective school regarding scholarships or grants available to students who are pursuing biological studies.

There may be opportunities for assistance based on your concentration or prior academic work. Some employers also provide tuition assistance or reimbursement to workers who are pursuing higher education.

What Can You Do with a Doctorate in Biology?

Earning a doctorate degree in biology can help you advance your professional qualifications and skill sets in your chosen area of concentration.

Biological sciences impact much of the world around us. For instance, some graduates choose to go into the field and research various species directly, while others work in a lab, concentrating on genetic development or microbiology. After graduation, some professionals choose to continue their research or pursue a role as an educator and mentor. Others go on to become biochemists, biophysicists, or medical scientists.

Biologists are employed in a variety of sectors, and your chosen doctoral track will impact your qualifications for various career paths.

How Long Does It Take to Get a PhD in Biology?

The length of time it takes to complete a PhD in Biology can depend on several factors, including any field work or dissertation work that is part of the program.

Generally speaking, a doctorate degree in biology takes between 3 years and 5 years to complete with full-time study. This also depends on the number of credit hours required by the program. Part-time enrollment will often extend your time to completion.

A program that does not ask students to complete a dissertation can potentially be completed in 3 years with full-time study.

Is Getting a PhD in Biology Worth It?

Yes, getting a PhD in Biology is worth it for many professionals. Those with a PhD in Biology have unique insight into how our lives are impacted by our own genetics, parasites, environmental factors, and more. This may be why careers in biological fields are on the rise.

Overall, the Bureau of Labor Statistics projects 8% job growth for life, physical, and social science occupations over the next ten years. A PhD can also help you qualify for positions in research and academia. Selecting a career path in biological sciences can allow greater insight into why our world is the way it is.

Earning Your Doctoral Degree in Biology Online

If you have a significant interest in the biological sciences, earning your doctorate degree in biology online can allow you to develop your expertise in the specialty of your choosing.

A PhD program will also enable you to contribute research to the field. Many doctoral students go on to pursue positions in research and academia, while others pursue advanced roles in the field. A number of accredited universities now offer both masters degree in biology online programs as well as doctoral programs online, catering to working professionals.

If you’re ready to get started on the next steps in your education and career, you can check out available biology doctoral programs offered online by accredited schools.