computational biology phd in usa

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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] )

Link to external website (http://www.berkeley.edu)

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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

Computational and Systems Biology PhD Program

Computational and systems biology.

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.

CSB Faculty and Research

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 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 computational biology and bioinformatics, gene and protein networks, regulatory genomics, molecular biophysics, instrumentation engineering, cell and tissue engineering, predictive toxicology and metabolic engineering, imaging and image informatics, nanobiology and microsystems, biological design and synthetic biology, neurosystems biology, and cancer biology.

The CSB PhD Program

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.

CSB Graduate Education

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 fall into three areas described below.

Modern Biology (One Subject): A term of modern biology at MIT strengthens the biology base of all students in the program. Subjects in biochemistry, genetics, cell biology, molecular biology, or neurobiology fulfill this requirement. The particular course taken by each student will depend on their background and will be determined in consultation with graduate committee members.

Computational Biology (One Subject): A term of computational biology provides students with a background in the application of computation to biology, including analysis and modeling of sequence, structural, and systems data. This requirement can be fulfilled by 7.91[J] / 20.490[J] Foundations of Computational and Systems Biology.

Topics in Computational and Systems Biology (One Subject): All first-year students in the program participate in / 7.89[J] Topics in Computational and Systems Biology, an exploration of problems and approaches in the field of computational and systems biology through in-depth discussion and critical analysis of selected primary research papers. This subject is restricted to first-year PhD students in CSB or related fields in order to build a strong community among the class. It is the only subject in the program with such a limitation.

Research Group Rotations (Three Rotations): To assist students with lab selection and provide a range of research activities in computational and systems biology, students participate in three research rotations of one to two months' duration during their first year. Students are encouraged to gain experience in experimental and computational approaches taken across different disciplines at MIT.

Advanced Electives

The requirement of four advanced electives is designed to develop both breadth and depth. The electives add to the base of the diversified core and contribute strength in areas related to student interest and research direction. To develop depth, two of the four advanced electives must be in the same research area or department. To develop breadth, at least one of the electives must be in engineering and at least one in science. 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: As is typical for students in other doctoral programs at MIT, 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 fourth 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.

Joint Carnegie Mellon-University of Pittsburgh Ph.D. Program in Computational Biology

Carl kingsford elected 2024 iscb fellow, similar genetic elements underlie vocal learning in mammals, logan and pfenning labs publish in nature communications, cpcb faculty and students win first place in cache challenge.

The Joint C MU- P itt Ph.D. Program in C omputational B iology (CPCB) provides interdisciplinary training in using quantitative and computational approaches to tackle scientific questions that lie at the interface of the life, physical, engineering, and computer sciences. CPCB trainees are taught and mentored by leading experts at two of the foremost computer science and biomedical research institutions in the world.

The program provides students with interdisciplinary training in various fields of computational biology: Cellular and Systems Modeling, Computational Structural Biology, Bioimage Informatics, and Computational Genomics. CPCB students also benefit from numerous professional development opportunities available at both host institutions. Together, the CPCB program positions our students to be leaders in this exciting field of biology and has prepared our graduates to go on to successful careers in both academia, industry, and beyond!

The program currently has 91 students, who are taught and mentored by leading experts at two of the foremost computer science and biomedical research institutions in the world. Students receive interdisciplinary training from 57 core faculty and 57 affiliated faculty, representing over 30 departments and centers in the universities.

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.

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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.

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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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] .

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

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Genomics and Computational Biology, PhD

Genomics and computational biology are now at the center of biomedical research. These disciplines take a holistic approach to ask about the origins, functions, and interactions of whole systems, using both experimental and theoretical work. Therefore, these studies require knowledge, skills, and, most importantly, synthesis and integration of biology, computer science, mathematics, statistics, and engineering.

This synthesis and integration requires a new generation of scientists that thrives in cross-disciplinary research. This can include molecular, cellular, and organismal biology (including genetics), mathematics, statistics, chemistry, and engineering. The goal of the GCB program is to train students that are experts in one or more of these disciplines and well versed in the others. We provide a comprehensive training program in Genomics and Computational Biology that gives students a broad foundation in the biological and quantitative sciences along with practical experience in computational and experimental genomics. The knowledge gained in this program will serve students in their careers as technology progresses.

For more information: https://www.med.upenn.edu/gcb/

View the University’s Academic Rules for PhD Programs .

Required Courses

The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2023 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.

Sample Plan of Study

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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

Biomedical Graduate Studies

Graduate group in genomics and computational biology.

Thank you for your interest in the University of Pennsylvania’s doctoral program in Genomics and Computational Biology (GCB).

It is an incredibly exciting and important time in Biomedical research. The speed in which new, rich, but increasingly massive “Big Data” sets can be generated to address fundamental questions in Biology and Medicine is truly mind-boggling. Fully taking advantage of these - and future - data types demands a new level of depth and breadth of biological knowledge paired with technical, mathematical, and computational sophistication in scientific inquiry. Our objective is to prepare students to become future leaders in this new, interdisciplinary era by pioneering biological discoveries across a range of important problems. The Biomedical Graduate Studies (BGS) umbrella is the administrative home for all graduate groups that confer a PhD in basic, biomedical sciences at the University of Pennsylvania, and where your application will be submitted. General admission information, as well as a link to the online application system, can be obtained from the BGS Website . BGS only accepts electronic applications, and the application process for each academic year begins in October of the previous year. Admissions to our program are based on basic training including (but not limited to): molecular biology, genetics, statistics/mathematics, and/or computer science. Because our program focuses at its core on interdisciplinary study, students with prior training in more than one area are encouraged to apply. Of course, exceptional students demonstrating mastery in a single field wishing to develop their interdisciplinary repertoire of skills will also be considered. The GCB admissions committee considers all components holistically when evaluating applicants to the program. Those components include their academic transcript, statement of research interests, their personal statements, and letters of recommendation. In your statements, we encourage you to share your personal history and lived experiences that demonstrate your resolve, enthusiasm, and how you got to the scientific areas and desired training that you are seeking. In addition, interviews are required as part of the admissions process. Applicants invited for an interview will be notified in December/January. Admissions decisions will be made in late February/early March, with all decisions finalized in April. All students accepted for admission into the PhD program receive tuition and health insurance coverage, plus a twelve-month stipend for living expenses. In addition, applicants are encouraged to apply for scholarships from prestigious funding sources such as the National Science Foundation and the National Institutes of Health. Are you up for the challenge? We look forward to your application.

Sincerely, Benjamin F. Voight, PhD Chair of GCB

Bioinformatics & Computational Biology Graduate Program

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About the Bioinformatics and Computational Biology Graduate Program

Iowa State University has been recognized as one of the top Bioinformatics and Computational Biology (BCB) PhD programs in the nation.

The Iowa State University Bioinformatics and Computational Biology (BCB) Program offers Ph.D. training at the intersections of Biological, Computing and Information Sciences. BCB alums have achieved superior outcomes in the academic, industrial and public sectors.

The BCB Graduate program is one of the first Bioinformatics and Computational Biology PhD programs in the United States. A history of the BCB program is here .

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gene expression and regulation •DNA, RNA, and protein sequence, structure, and interactions • molecular evolution • protein design • network and systems biology • cell and tissue form and function • disease gene mapping • machine learning • quantitative and analytical modeling

David Bartel

Christopher burge, olivia corradin, amy e. keating, eric s. lander, douglas lauffenburger, gene-wei li, adam c. martin, sergey ovchinnikov, david c. page, peter reddien, francisco j. sánchez-rivera, brandon (brady) weissbourd, jonathan weissman, harikesh s. wong, michael b. yaffe.

Jonathan Weissman investigates how proteins fold into their correct shape and how misfolding impacts disease and normal physiology, while building innovative tools for exploring the organizational principles of biological systems.

Scientists develop a rapid gene-editing screen to find effects of cancer mutations

Uncovering answers to longstanding questions about sex differences in autoimmune and neurodegenerative diseases

De-tail-ing RNA regulation in eggs and early embryos

How signaling proteins get to the mitochondrial surface

Blood cell family trees trace how production changes with aging

Sex chromosomes responsible for much more than determining sex

Cell fate choice during adult regeneration is highly disorganized, new study finds

Machine learning helps predict drugs’ favorite subcellular haunts

Computational Biology Graduate Programs in America

1-18 of 18 results

MIT School of Science

Cambridge, MA •

Massachusetts Institute of Technology •

Graduate School

Massachusetts Institute of Technology ,

Graduate School ,

CAMBRIDGE, MA ,

Harvard John A. Paulson School of Engineering and Applied Sciences

Harvard University •

Harvard University ,

Princeton University

Princeton, NJ •

• Rating 4.33 out of 5 3 reviews

Master's Student: The best part of the Princeton University mechanical engineering graduate degree is the excellent faculty that teach the courses. They are incredibly knowledgeable and also very willing to help students in office hours or in sponsorship of projects. The worst part of the Princeton University mechanical engineering graduate degree is the lack of structure for the graduate research program which can leave you feeling unsure on the direction of your research. ... Read 3 reviews

PRINCETON, NJ ,

3 Niche users give it an average review of 4.3 stars.

Featured Review: Master's Student says The best part of the Princeton University mechanical engineering graduate degree is the excellent faculty that teach the courses. They are incredibly knowledgeable and also very willing to help... .

Read 3 reviews.

University of Pittsburgh

Graduate School •

PITTSBURGH, PA

• Rating 4.43 out of 5 74

Kenneth P. Dietrich School of Arts and Sciences

University of Pittsburgh •

Mississippi State University

MISSISSIPPI STATE, MS

• Rating 4.51 out of 5 49

Brown University Graduate School

Providence, RI •

Brown University •

Brown University ,

PROVIDENCE, RI ,

Dornsife College of Letters, Arts and Sciences

Los Angeles, CA •

University of Southern California •

University of Southern California ,

LOS ANGELES, CA ,

Cornell University College of Agriculture and Life Sciences

Ithaca, NY •

Cornell University •

Cornell University ,

ITHACA, NY ,

Find college scholarships

Weill Cornell Graduate School of Medical Sciences

New York, NY •

• Rating 4.75 out of 5 4 reviews

Doctoral Student: The coursework was relevant, a little disjointed but good. There could be a wider range of courses that would be great, but it’s nice that we can take courses from other universities. ... Read 4 reviews

NEW YORK, NY ,

4 Niche users give it an average review of 4.8 stars.

Featured Review: Doctoral Student says The coursework was relevant, a little disjointed but good. There could be a wider range of courses that would be great, but it’s nice that we can take courses from other universities. .

Read 4 reviews.

Mellon College of Science

Pittsburgh, PA •

Carnegie Mellon University •

Blue checkmark.

Carnegie Mellon University ,

PITTSBURGH, PA ,

UC Berkeley College of Letters & Science

Berkeley, CA •

University of California - Berkeley •

University of California - Berkeley ,

BERKELEY, CA ,

Case Western Reserve University School of Dental Medicine

Cleveland, OH •

Case Western Reserve University •

Case Western Reserve University ,

CLEVELAND, OH ,

University of Pittsburgh ,

College of Liberal Arts & Sciences - The University of Kansas

Lawrence, KS •

The University of Kansas •

The University of Kansas ,

LAWRENCE, KS ,

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Genetics and Genomics Graduate Programs
Physiology and Pathology Graduate Programs

CU Anschutz Medical Campus Graduate School

Aurora, CO •

University of Colorado Denver •

• Rating 4.41 out of 5 29 reviews

Master's Student: Really great online programs with personalized attention, lots of organized online resources, and interesting classes and programs ... Read 29 reviews

University of Colorado Denver ,

AURORA, CO ,

29 Niche users give it an average review of 4.4 stars.

Featured Review: Master's Student says Really great online programs with personalized attention, lots of organized online resources, and interesting classes and programs .

Read 29 reviews.

University of Texas - Arlington College of Science

Arlington, TX •

University of Texas - Arlington •

University of Texas - Arlington ,

ARLINGTON, TX ,

The Graduate School - Rutgers University - Camden

Camden, NJ •

Rutgers University - Camden •

• Rating 5 out of 5 4 reviews

Master's Student: Rigorous and challenging but definitely the push I needed to gain opportunities in the professional field of public service. The academics at Rutgers-Camden fosters an eager environment that promotes diversity, group support, and the understanding of development in a well-rounded setting. The professional field of public administration is forever evolving and I feel confident that my education has prepared me to be a resilient, open minded, and capacity building leader to help make this world a better fit for all. I have been able to gain more knowledge of the principles of humanitarian aid as well as local and national policies. ... Read 4 reviews

Rutgers University - Camden ,

CAMDEN, NJ ,

4 Niche users give it an average review of 5 stars.

Featured Review: Master's Student says Rigorous and challenging but definitely the push I needed to gain opportunities in the professional field of public service. The academics at Rutgers-Camden fosters an eager environment that promotes... .

McGovern Medical School

Houston, TX •

University of Texas - Health Science Center at Houston •

• Rating 5 out of 5 3 reviews

Niche User: The cardiac perfusion program is only 1 year long! The program does not require you to live on campus ! It’s not very expensive either ! ... Read 3 reviews

University of Texas - Health Science Center at Houston ,

HOUSTON, TX ,

3 Niche users give it an average review of 5 stars.

Featured Review: Niche User says The cardiac perfusion program is only 1 year long! The program does not require you to live on campus ! It’s not very expensive either ! .

Weill Cornell Medical College

• Rating 5 out of 5 1 review

Graduate Student: I like the diversity and the awesome possibilities. As a researcher there are nearly no limits as propper equipments and needed experts of nearly anything are mostly all in close proximity. ... Read 1 review

1 Niche users give it an average review of 5 stars.

Featured Review: Graduate Student says I like the diversity and the awesome possibilities. As a researcher there are nearly no limits as propper equipments and needed experts of nearly anything are mostly all in close proximity. .

Read 1 reviews.

Graduate School of Biomedical Sciences - Baylor College of Medicine

Baylor College of Medicine •

Baylor College of Medicine ,

Showing results 1 through 18 of 18

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Computational Biology

The Department of Computational Biology consists of faculty members with expertise in computer science, genomics, systems biology, population genetics and modeling. They apply these skills to a wide range of exciting problems in the life sciences.

The department administers the Computational Biology undergraduate concentration within the Bachelor of Science degree in Biology . Additionally, the faculty in the department are members of the Computational Biology graduate field , as well as several other graduate fields offering M.Sc. and Ph.D. degrees .

Related Groups

Statistical & Data Science
Department of Mathematics
Molecular Biology & Genetics
Operations Research & Information Engineering
Cornell Population Center
Cornell Statistical Consulting Unit

Related Fields

Applied Mathematics
Genetics, Genomics and Development
Mathematics
Operations Research
Statistical Science
Computer Science

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Comp Bio in the news

American Indian and Indigenous Studies Program
Biological and Environmental Engineering

Hands holding a positive pregnancy test.

A new study testing the accuracy of existing methods used to predict the genetic variation that cause infertility found that relying on computational or in vitro experiments alone is insufficient.

100 Best colleges for Bioinformatics and Computational biology in the United States

Updated: February 29, 2024

Art & Design
Computer Science
Engineering
Environmental Science
Liberal Arts & Social Sciences
Mathematics

Below is a list of best universities in the United States ranked based on their research performance in Bioinformatics and Computational biology. A graph of 50.6M citations received by 1.02M academic papers made by 542 universities in the United States was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. Harvard University

For Bioinformatics and Computational biology

2. Stanford University

3. Johns Hopkins University

4. University of California - San Francisco

5. Massachusetts Institute of Technology

6. University of Washington - Seattle

7. University of California-San Diego

8. University of Michigan - Ann Arbor

9. Yale University

10. University of Pennsylvania

11. University of California - Los Angeles

12. Cornell University

13. University of California - Berkeley

14. Washington University in St Louis

15. University of Texas MD Anderson Cancer Center

16. University of North Carolina at Chapel Hill

17. University of Wisconsin - Madison

18. Columbia University

19. Baylor College of Medicine

20. University of Chicago

21. University of Texas Southwestern Medical Center

22. Ohio State University

23. University of Minnesota - Twin Cities

24. University of Pittsburgh

25. Duke University

26. University of California - Davis

27. Boston University

28. New York University

29. Northwestern University

30. University of Southern California

31. Vanderbilt University

32. Icahn School of Medicine at Mount Sinai

33. University of Florida

34. Pennsylvania State University

35. University of Illinois at Urbana - Champaign

36. Emory University

37. University of Utah

38. California Institute of Technology

39. Mayo Clinic College of Medicine and Science

40. Rockefeller University

41. Rutgers University - New Brunswick

42. Princeton University

43. University of Virginia

44. Case Western Reserve University

45. University of Colorado Boulder

46. University of Arizona

47. University of Texas at Austin

48. University of Alabama at Birmingham

49. Indiana University - Purdue University - Indianapolis

50. University of Massachusetts Medical School Worcester

51. University of Maryland, Baltimore

52. University of Colorado Denver/Anschutz Medical Campus

53. University of California - Irvine

54. University of Maryland - College Park

55. Seattle University

56. University of Illinois at Chicago

57. Michigan State University

58. University of Iowa

59. Oregon Health & Science University

60. Washington State University

61. University of Georgia

62. Tufts University

63. University at Buffalo

64. Purdue University

65. Iowa State University

66. Wayne State University

67. University of Miami

68. Texas A&M University - College Station

69. North Carolina State University at Raleigh

70. Georgetown University

71. University of Kentucky

72. University of Texas Health Science Center at Houston

73. Brown University

74. Georgia Institute of Technology

75. Arizona State University - Tempe

76. University of Texas Health Science Center at San Antonio

77. University of Rochester

78. Providence College

79. University of California - Santa Cruz

80. Stony Brook University

81. Thomas Jefferson University

82. University of Missouri - Columbia

83. Dartmouth College

84. Wake Forest University

85. University of California - Riverside

86. Virginia Commonwealth University

87. Medical University of South Carolina

88. University of Connecticut

89. University of South Florida

90. University of Cincinnati

91. University of New Mexico

92. Virginia Polytechnic Institute and State University

93. Medical College of Wisconsin

94. University of Tennessee - Knoxville

95. Oregon State University

96. Sanford Burnham Prebys Medical Discovery Institute

97. united states military academy.

98. Colorado State University - Fort Collins

99. George Washington University

100. University of Kansas

The best cities to study Bioinformatics and Computational biology in the United States based on the number of universities and their ranks are Cambridge , Stanford , Baltimore , and San Francisco .

Biology subfields in the United States

Equity & Inclusion

Groundbreaking computational precision health program appoints 13 new faculty

Woman with head resting on hand looking at computer monitor with lines of text on it

The UCSF-UC Berkeley Joint Program in Computational Precision Health (CPH) has appointed 13 new faculty to its augmented graduate group, which functions as a novel, bi-campus initiative and PhD program.

These UC community members bring expertise in machine learning for biomedical applications, human-computer interaction, and technology-based interventions to address health disparities to this groundbreaking program. Dr. Ida Sim, CPH co-director and professor of medicine at UCSF, called the group “ the heart of the CPH intellectual community.” CPH aims to transform personal and public health through computation by developing and deploying adaptive precision interventions for real-world impact.

“Interest in computational precision health continues to grow, and we are so honored to have these new members from across both institutions bring their clinical and research expertise to our shared vision of transforming health through computation,” said Sim.

“The incredible range of stellar faculty are addressing the staggering complexity of health and healthcare systems, and we are thrilled to work on solutions with real-world impact with this community," she said.

These latest appointments grow the augmented graduate group to 55 members, more than halfway to the CPH’s hoped-for size of up to 80 faculty. The members include Berkeley’s Adrian Aguilera , Joe Lewnard and Niloufar Salehi and UCSF’s Reza Abbasi-Asl , Katrina Abuabara , Rima Arnout , Jean Feng , A. Jay Holmgren , Sharmila Majumdar , Pratik Mukherjee , Sara Murray , Srikantan Nagarajan and Isabel Rodriguez-Barraquer .

Launched in October 2021, CPH draws upon two world-renowned universities’ data science, computing, biomedicine and health leaders to forge a new field with the capacity to transform health. CPH researchers will develop computational breakthroughs to enable complex care – from individuals to public health – by augmenting human intelligence and implementing data-informed interventions in hospitals, clinics and the community.

At UC Berkeley, the program is administered by the Division of Computing, Data Science, and Society (CDSS) and exemplifies CDSS’ efforts to create interdisciplinary fields that use data science to solve real-world challenges.

The next generation of researchers

This milestone comes as CPH makes major strides toward welcoming its first student cohort to its Ph.D. and second cohort to the designated emphasis. CPH received more than 200 applications to join its first Ph.D. cohort , which has spots available for just eight students.

Eligible UCSF and Berkeley doctoral students will be able to apply for the program’s designated emphasis starting March 1. Students accepted to the designated emphasis take CPH courses as an interdisciplinary specialization that compliments their doctoral degree studies, and are part of the community of CPH faculty and students, offering unique cross-campus connections and opportunities.

"The sheer number and exceptional quality of applicants for our new Ph.D. program in computational precision health is a testament to the growing excitement in this emerging field,” said Ahmed Alaa, a CPH assistant professor. “It highlights the unique and vital role that this type of graduate training can play in advancing the field of precision health and shaping the future of medicine."

Diversity, Equity, and Inclusion

Message from the director.

A welcome message from Sabrina Diano, PhD, Director, Institute of Human Nutrition.

IHN alumni are advancing nutrition around the world through work in the health care industry, clinical research, medical education, and more.

Research Laboratories

Learn more about the Institute for Human Nutrition's research.

In the Community

Local initiatives.

IHN is a proud supporter of local organizations and activities here in Washington Heights and the surrounding communities.

PhD in Nutritional and Metabolic Biology

The Nutritional and Metabolic Biology (NMB) PhD training program prepares students to work at the frontiers of biomedical research in nutritional and metabolic sciences, exploring the role of nutrition in maintaining optimal human health. The objective of the training program is to prepare individuals who will conduct original basic science research, teach in medical schools and universities, and hold positions of leadership in community and international nutrition.

Housed within the Institute of Human Nutrition (IHN) at Columbia University Medical Center (CUMC), this inter-disciplinary and multi-departmental training program is highly structured and comprises both coursework and basic research. The NMB program is one of the few pre-doctoral training programs in nutrition in the United States that is located within a medical school and is unique among the other PhD programs at CUMC with an equal number of MDs and PhDs as faculty mentors (including ten MD/PhDs). The location of the NMB training program in a medical school offers trainees a wide array of research opportunities in laboratories headed by established senior scientists as well as NIH-funded younger independent investigators, all focused on the role of nutrition and metabolism in health and disease.

nmb_phd_program_faculty_-_life_at_columbia

nmb_phd_program_students_-_life_at_columbia

For information on NMB faculty, please visit the Faculty page on the Graduate School of Arts and Sciences (GSAS) site .

Lori Zeltser, PhD

Co-director

Anthony Ferrante Jr., MD, PhD

IMAGES

What Is Computational Biology?
Ph.D. Programme in Computational Biology
Molecular & Computational Biology phd program
IMSC Computational Biology PhD Program 2020
What is Computational Biology? The Computational Biology Major at Carnegie Mellon University
Computational Biology and Biostatistics, Master of Science

VIDEO

Computational Biology #biotechnology #molecularbiology #bioinformatics #agribtechbiotechnolgy
Computational Biology
Computational Biology Summer Research Programme 2024 at IMSc
Introduction to computational Biology
Computational Biology, Stockholm
Computational Biology India Symposium CBInd 2023-24

COMMENTS

Computational Biology PhD
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). ... 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 ...
Ph.D. programs in Computational Biology at JHU
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.
Quantitative and Computational Biology
The Program in Quantitative and Computational Biology (QCB) is intended to facilitate graduate education at Princeton at the interface of biology and the more quantitative sciences and computation. Administered from The Lewis-Sigler Institute for Integrative Genomics, QCB is a collaboration in multidisciplinary graduate education among faculty ...
Welcome to the MIT Computational and Systems Biology PhD ...
Please join us for this week's CSB seminar this Wednesday 2/28, from 4-5pm in 32-124. ... MIT Computational & Systems Biology PhD Program (CSB) Massachusetts Institute of Technology 77 Massachusetts Avenue Bldg 68, Room 120C Cambridge, MA 02139. [email protected] 617.324.4144.
Computational and Systems Biology PhD Program
The CSB PhD Program. 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 ...
Carnegie Mellon-University of Pittsburgh Ph.D. Program in Computational
The Joint CMU-Pitt Ph.D. Program in Computational Biology (CPCB) provides interdisciplinary training in using quantitative and computational approaches to tackle scientific questions that lie at the interface of the life, physical, engineering, and computer sciences. CPCB trainees are taught and mentored by leading experts at two of the foremost computer science and biomedical research ...
Computational Biology Program
The Computational Biology Ph.D. program is training the next generation of Computational Scientists to tackle research using the big genomic, image, remote sensing, clinical, and real world data that are transforming the biological sciences. The graduate field of Computational Biology offers Ph.D. degrees in the development and application of ...
Computational Biology
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 ...
Computational and Systems Biology < MIT
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 ...
Computational Biology PhD Program
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 ...
Ph.D. in Computational Biology and Bioinformatics
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 ...
Genomics and Computational Biology, PhD
Genomics and computational biology are now at the center of biomedical research. These disciplines take a holistic approach to ask about the origins, functions, and interactions of whole systems, using both experimental and theoretical work. Therefore, these studies require knowledge, skills, and, most importantly, synthesis and integration of ...
Computational Biology
Overview. 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 ...
Admissions
The mission of the Graduate Group in Genomics and Computational Biology (GCB) ... All students accepted for admission into the PhD program receive tuition and health insurance coverage, plus a twelve-month stipend for living expenses. In addition, applicants are encouraged to apply for scholarships from prestigious funding sources such as the ...
Bioinformatics & Computational Biology Graduate Program
The BCB Graduate program is one of the first Bioinformatics and Computational Biology PhD programs in the United States. A history of the BCB program is here. Make a Gift. ISU researcher wins innovation challenge to seek RNA drug targets. Jan 16, 2024.
Bioinformatics and Computational Biology (Ph.D.)
The Ph.D. in Bioinformatics and Computational Biology is an interdisciplinary program that provides students with the skills and knowledge to analyze large scale biological data and develop new computational strategies. BCB PhD graduates are employed worldwide in academia and industry. Key program application deadlines: Jan. 1 for Fall ...
Bioinformatics and Computational Biology (PhD)
Researchers in the field of bioinformatics and computational biology collect, store, analyze, and present complex biological data using high-performance computing. Through this work, critical contributions are made to disease detection, drug design, forensics, agriculture, and environmental sciences. This research-oriented program trains a new ...
Computational Biology
gene expression and regulation •DNA, RNA, and protein sequence, structure, and interactions • molecular evolution • protein design • network and systems biology • cell and tissue form and function • disease gene mapping • machine learning • quantitative and analytical modeling
2023-2024 Top Computational Biology Graduate Programs
Princeton University. Princeton, NJ •. Graduate School. •. 3 reviews. Master's Student: The best part of the Princeton University mechanical engineering graduate degree is the excellent faculty that teach the courses. They are incredibly knowledgeable and also very willing to help students in office hours or in sponsorship of projects.
Computational Biology
The Department of Computational Biology consists of faculty members with expertise in computer science, genomics, systems biology, population genetics and modeling. They apply these skills to a wide range of exciting problems in the life sciences. The department administers the Computational Biology undergraduate concentration within the ...
Best Bioinformatics and Computational biology colleges in the US [Rankings]
Below is the list of 100 best universities for Bioinformatics and Computational biology in the United States ranked based on their research performance: a graph of 50.6M citations received by 1.02M academic papers made by these universities was used to calculate ratings and create the top.
Groundbreaking computational precision health program appoints 13 new
The UCSF-UC Berkeley Joint Program in Computational Precision Health (CPH) has appointed 13 new faculty to its augmented graduate group, which functions as a novel, bi-campus initiative and PhD program. These UC community members bring expertise in machine learning for biomedical applications, human-computer interaction, and technology-based interventions to address health disparities to this ...
PhD in Nutritional and Metabolic Biology
The Nutritional and Metabolic Biology (NMB) PhD training program prepares students to work at the frontiers of biomedical research in nutritional and metabolic sciences, exploring the role of nutrition in maintaining optimal human health. The objective of the training program is to prepare individuals who will conduct original basic science ...