A&S—Computational Biology
Joint Pitt-CMU PhD Program in Computational Biology
Ivet Bahar and Robert F. Murphy, Directors
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 behavior 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
University of Pittsburgh:
Ivet Bahar, Ph.D.
Director, Joint CMU-Pitt Ph.D. Program in Computational Biology
Department of Computational Biology
School of Medicine, University of Pittsburgh
3501 Fifth Avenue, BST3, Room 3058
Pittsburgh, PA 15260
412-648-3332 (phone)
412-648-3163 (fax)
bahar@ccbb.pitt.edu
Judy Wieber, Ph.D.
Coordinator, Joint CMU-Pitt Ph.D. Program in Computational Biology
Department of Computational Biology
School of Medicine, University of Pittsburgh
3501 Fifth Avenue, BST3, Room 3081
Pittsburgh, PA 15260
412-648-8646 (phone)
412-648-3163 (fax)
jwieber@ccbb.pitt.edu
Carnegie Mellon University:
Robert F. Murphy, Ph.D.
Director, Joint CMU-Pitt Ph.D. Program in Computational Biology
Carnegie Mellon University
4400 Fifth Avenue
Pittsburgh, PA 15213
412-268-3480 (phone)
412-268-9580 (fax)
murphy@cmu.edu
Program Web site: www.ccbb.pitt.edu/compbio/
Admissions
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 Ph.D. in computational biology, prerequisites in life sciences, computer science, physical sciences, mathematics, statistics, and computational biology are recommended. Students whose backgrounds does not include these courses may be admitted with the additional requirement to take appropriate compensating classes. For more information on prerequisites, visit www.ccbb.pitt.edu/compbio/Admissions/prerequisites.html.
Application
The application receipt deadline is January 15. Required application materials include:
- Completed online application
- Three letters of recommendation
- Official transcripts from all colleges and universities attended
- Official report of GRE scores (general, required; subject, recommended)
- Official report of TOEFL score (required for foreign applicants from countries other than Canada, Australia, the United Kingdom, or New Zealand)
- Application fee of $50
Applications are reviewed by the Joint CMU-Pitt Ph.D. Program in Computational Biology. Each admitted student is assigned an initial research advisor and receives an admissions offer letter from the university at which that advisor holds his/her primary appointment. 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 the application process, see www.ccbb.pitt.edu/compbio/Admissions/.
Financial Aid
All students are provided with a stipend and full tuition remission. Assistance is also provided for health insurance.
Teaching Assistantships
There is no formal teaching requirement in the program. However, if the resources are available, interested students may participate in currently available courses that utilize graduate student teaching assistants. Students are encouraged to develop teaching skills by mentoring other students and passing on their knowledge to lab mates and fellow students.
Curriculum
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-plus are formal coursework, and the remaining to be completed with full-time research.
All students are required to take five of six 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
- Algorithms
- Machine Learning
- Computational Genomics
- Computational Structural Biology
- Cellular and Systems Modeling
- Computational Biology Wet Lab
All students are required to take graduate elective courses. The first elective should be a life science/physical science course, specified for a student's chosen area of specialization. Three additional elective courses must be drawn from that area of specialization and one may be from any area.
Specialization Areas
- Computational Genomics
- Computational Structural Biology
- Cellular and Systems Modeling
- Bioimage Informatics
- Computational Neurobiology
For more information on the curriculum, see www.ccbb.pitt.edu/compbio/Curriculum/.
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 the third year, students present their research progress to fellow students and the faculty on at least an annual basis.
Journal Club
Effective presentation of scientific data is an invaluable aspect of graduate training. Therefore, all 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 basis presentation skills. Students subsequently receive feedback on their talks, thereby improving their presentation skills as their graduate training services.
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.
Scheduling
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 semesters (50 to 75 percent 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 semesters would be split between taking electives and doing research.
Students who enter with some biology or computer science background but not with sufficient background to take all of the core course would take a mix of missing prerequisites and core courses in each of the first two semesters (approximately 90 percent time) and spend 10 percent time on research. These students would then take a mix of remaining core courses and electives in the third and fourth semesters (along with 30 percent research) and finish electives in the fifth and/or sixth semesters.
Comprehensive Examination
Students are required to pass a comprehensive examination after completion of their 27 credits (core plus elective) requirement, prior to being officially admitted to candidacy to the Ph.D. degree. Students are expected to complete this examination no later than the spring semester of their third year, and can take it as early as the end of the fall semester of the second year. The comprehensive examination consists of two parts: a 15-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 Ph.D. candidacy conduct research on a full-time basis, and are required to complete a minimum of 40 credit hours (9 credits per semester) 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 27 credit hours of core plus 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 Masters Degree
The program does not admit students whose goal is to attain a Master's of Science degree. However, it might become necessary for a Ph.D. student to transfer to an M.S. 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.
Training Faculty
The program provides students with cross-disciplinary training in established as well as newly emerging fields of computational biology. Students have access to a community of faculty mentors from the University of Pittsburgh and Carnegie Mellon University, which not only provides a breadth of research areas for investigation, but also offers the technical and intellectual resources to make rapid progress toward their doctoral degree.
For a list of training faculty, see www.ccbb.pitt.edu/compbio/Faculty.
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