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University of Pittsburgh    
2023-2024 Graduate & Professional Studies Catalog 
  Jun 12, 2024
2023-2024 Graduate & Professional Studies Catalog

Computational Biology (PhD)

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Computational biology is defined as the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological, behavioral, and social systems.* It is an interdisciplinary approach that draws from specific disciplines such as mathematics, physics, computer science and engineering, biology, and behavioral science.

The Joint Pitt-CMU PhD Program in Computational Biology is an intensive, interdisciplinary training program that provides students with a deep understanding of the current state of the art in computational biology. Students in this program acquire the quantitative background and research skills needed to advance the field of computational biology. In addition, they develop the critical thinking skills needed to appreciate the potential, strength, and limitations of computational, mathematical, and engineering tools for tackling biological problems.

*NIH Working Definition, July 17, 2000.

Contact Information

James Faeder, PhD
Associate Professor
Department of Computational & Systems Biology
School of Medicine, University of Pittsburgh
800 Murdoch I Building, Room 839
3420 Forbes Ave
Pittsburgh, PA 15260
Phone: 412-648-8171
Fax: 412-648-3163
Program Coordinator:
Kelly Gentille
Educational Programs Administrator
Department of Computational and Systems Biology
School of Medicine, University of Pittsburgh
800 Murdoch I Building, Room 839
3420 Forbes Ave
Pittsburgh, PA 15260
Phone: 412-648-8107
Fax: 412-648-3163
Program Website:                       



The interdisciplinary character of the program is unique and distinct from many other programs that are focused toward a specific discipline. The program seeks outstanding students from the biological, physical and computational sciences, and engineering. For example, computational biology majors, or double majors in biology and quantitative sciences are ideal candidates.

Recommended Prerequisites

For students planning their undergraduate course schedules in anticipation of applying for the PhD in computational biology, prerequisites in life sciences, computer science, physical sciences, mathematics, statistics, and computational biology are recommended. Students whose background does not include these courses may be admitted with the additional requirement to take appropriate compensating classes. For more information on prerequisites, see


REQUIRED MATERIALS - Deadline December 10, 2019

  • The Online Application
  • Statement of Purpose
  • Three letters of Recommendation
  • Unofficial Transcripts (submitted online)
  • Conversion of GPA (for international students only)
  • Unofficial TOEFL Scores (submitted online)
  • Application Fee

Applications are reviewed by the Joint CMU-Pitt PhD Program in Computational Biology. Each admitted student is assigned an initial university of matriculation, and receives an admissions offer letter from that university. Incoming students can be placed directly in a laboratory (if mutual interest exists between a student and an advisor), or go through a period of three rotations, after which the student chooses an advisor. Students have the ability to change advisors (subject to agreement of the new advisor and availability of support) and to transfer between the two universities to reflect advisor changes.

For more information on application process, see

Financial Aid

All students are provided with a stipend and full tuition remission. Assistance is also provided for health insurance.

Teaching Assistantships

Although all students are supported as research assistants throughout their time in the program, students are required to TA for one semester.  There are also opportunities to assist in the teaching courses of the program. Students are also encouraged to develop teaching skills by mentoring other students and passing on their knowledge to lab mates and fellow students.


The curriculum is designed to train students who will shape the next generation of discovery in computational biology in academia and industry. Students are required to complete 72 credit hours of academic work toward partial fulfillment of the requirements for completion of dissertation study. Of these, 30+ are formal coursework, and the remaining to be completed with full-time research.

All students are required to take five core graduate courses. The core courses aim at providing a strong common background in computational biology before they specialize in particular research areas

Core Courses

  • Machine Learning
  • Introduction to Computational Structural Biology
  • Computational Genomics
  • Cellular and Systems Modeling
  • Laboratory Methods for Computational Biologists

In addition, all students are required to take three graduate elective courses: a life science/physical science course; an advanced interdisciplinary elective specified for the student’s chosen area of specialization; and one general elective.

Specialization Areas

  • Computational Genomics
  • Computational Structural Biology
  • Cellular and Systems Modeling
  • Bioimage Informatics

For more information on the curriculum, see

Other Courses

In addition to core and elective courses, students take complementing courses, if needed, and participate in program seminar, journal clubs, ethics courses and directed studies toward their dissertation projects.

Program Seminar Series

Students enrolled in the program are expected to attend scientific seminars during all years of training. Beginning in their second year and ending in the year before their thesis defense, students present their research progress to fellow students and the faculty on at least an annual basis.

CPCB Course

Effective presentation of scientific data is an invaluable aspect of graduate training. Therefore, all first- and second-year students must present a scientific article on a topic (selected by a faculty member) that introduces students to the methodology and applications of computational biology. The talk is made in a format that allows the student to develop basic presentation skills. Students subsequently receive feedback on their talks, thereby improving their presentations skills as their graduate training advances.

Training in Ethics

Ethical conduct and scientific integrity is an essential aspect of research. This is especially important given the competitive nature of funding processes and the high demand for productivity. Hence, the program instructs students on the significance and practice of ethical conduct.

Directed Study

Credits are given for laboratory projects (wet or computer labs) under the direction of the dissertation advisor prior to admission to candidacy for the doctorate.


We anticipate two types of course schedules for students in the program. The default for students who have taken the prerequisites will be to take three courses in each of the first two terms (50-75% time) and spend the remaining time on research. Such students would normally take the core courses in the first year along with one additional course. The third and fourth terms would be split between taking electives and doing research.

Students who enter with some biology or computer science or physical science background but not with sufficient background to take all of the core courses would take a mix of missing prerequisites and core courses in each of the first two terms (approx. 90% time) and spend 10% time on research. These students would then take a mix of remaining core courses and electives in the third and fourth terms (along with 30% research) and finish electives in the fifth and/or sixth terms.

Comprehensive Examination

Students are required to pass a comprehensive examination after completion of their courses, prior to being officially admitted to candidacy to the PhD degree. Students are expected to complete this examination no later than the beginning of the spring term of their third year. The comprehensive examination consists of two parts: a 12-page “grant-style” written proposal of the proposed research, followed by an oral defense of the proposed research.

Post-Comprehensive Qualifying Examination

Students who have been accepted to PhD candidacy conduct research on a full time basis, and are required to complete a minimum of 40 credit hours (9-14 credits per term) of full-time dissertation study in order to meet the criteria for dissertation defense. Hence, all students will have completed at least 72 credit hours of study prior to graduation, including 29 credit hours of core + elective courses, and at least 40 credit hours of dissertation research.

Completion of Degree

The program is structured in such a way that students can finish their degree within four years of entering their dissertation laboratory. However, it is recognized that the actual time required to attain the degree depends on the specific type of research undertaken and how quickly progress is made in completing the experimental program.

Terminal Master’s Degree

The Program does not admit students whose goal is to attain a MS degree. However, it might become necessary for a PhD student to transfer to an MS track for academic reasons or reasons beyond the student’s control, e.g., medical circumstances or a change in family circumstances necessitating a long-distance move.


For more information on the program, such as list of training faculty, please see

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