Quantitative and Computational Biology

Academic Year 2022 – 2023

General Information

Address
Carl Icahn Laboratory, Lewis-Sigler Institute for Integrative Genomics
Phone

Program Offerings:

  • Ph.D.

Director of Graduate Studies:

Graduate Program Administrator:

Overview

The Program in Quantitative and Computational Biology (QCB) is intended to facilitate graduate education at Princeton at the interface of biology, 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 in the Institute and the Departments of Chemistry, Chemical and Biological Engineering, Computer Science, Ecology and Evolutionary Biology, Molecular Biology, and Physics. The program covers the fields of genomics, computational biology, systems biology, quantitative genetics, molecular evolution, and microbial interactions.

Program Highlights

An Outstanding Tradition: Chartered in 1746, Princeton University has long been considered among the world’s most outstanding institutions of higher education, with particular strength in mathematics and the quantitative sciences. Building upon the legacies of greats such as Compton, Feynman, and Einstein, Princeton established the Lewis-Sigler Institute of Integrative Genomics in 1999 to carry this tradition of quantitative science into the realm of biology.

World Class Research: The Lewis-Sigler Institute and the QCB program focus on attacking problems of great fundamental significance using a mixture of theory and experimentation. To maximize the chances of paradigm-shifting advances, there is an emphasis on studying fundamental processes in biology, such as transcription and metabolism, in tractable model organisms including bacteria, yeasts, worms, and fruit flies.

World Class Faculty: The research efforts are led by the QCB program’s 40+ faculty, who include a Nobel Laureate, 8 members of the National Academy of Sciences, 4 Howard Hughes Investigators, and over a dozen early-career faculty who have received major national research awards (e.g., NSF CAREER or NIH Innovator).

Personalized Education: A hallmark of any Princeton education is personal attention. The QCB program is no exception. Lab sizes are generally modest, typically 6 – 16 researchers and all students have extensive direct contact with their faculty mentors. Many students choose to work at the interface of two different labs, enabling them to build close intellectual relationships with multiple principal investigators.

Stimulating Environment: The physical heart of the QCB program is the Carl Icahn Laboratory, an architectural landmark located adjacent to physics, biology, chemistry, neuroscience, and mathematics on Princeton’s main campus. Students have access to a wealth of resources, both intellectual and tangible, such as world-leading capabilities in DNA sequencing, mass spectrometry, and microscopy. They also benefit from the friendly atmosphere of the program, which includes tea and cookies every afternoon. When not busy doing science, students can partake in an active campus social scene and world-class arts and theater events on campus.

Apply

Application deadline
December 1, 11:59 p.m. Eastern Standard Time (This deadline is for applications for enrollment beginning in fall 2023)
Program length
5 years
Fee
$75
GRE
General Test not accepted

Program Offerings

Courses

Three courses, QCB 515, QCB 535, and COS/QCB 551, are required for all students, as is a Responsible Conduct in Research (RCR) course.  Two additional courses must be completed and can be chosen from the following lists.  Course selections must include at least one course from the quantitative courses list.  Courses not on the approved lists may be taken as electives with approval from the DGS.

Note: The full course of study must be reviewed and approved by the Director of Graduate Studies (DGS).

Quantitative Courses (must take at least one)

 

  • APC 524/MAE 506/AST 506 Software Engineering for Scientific Computing
  • CBE 517 Soft Matter Mechanics: Fundamentals & Applications
  • CHM 503/CBE 524/MSE 514 Introduction to Statistical Mechanics
  • CHM 515 Biophysical Chemistry I 
  • CHM 516 Biophysical Chemistry II
  • CHM 542 Principles of Macromolecular Structure: Protein Folding, Structure, and Design
  • COS 511 Theoretical Machine Learning
  • COS 524/COS 424 Fundamentals of Machine Learning
  • COS 597D Advanced Topics in Computer Science: Advanced Computational Genomics
  • COS 597F Advanced Topics in Computer Science: Computational Biology of Single Cells
  • ELE 535 Machine Learning and Pattern Recognition
  • MAE 567/CBE 568 Crowd Control: Understanding and Manipulating Collective Behaviors and Swarm Dynamics
  • MAE 550/MSE 560 Lessons from Biology for Engineering Tiny Devices
  • MAT 586/APC 511/MOL 511/QCB 513 Computational Methods in Cryo-Electron Microscopy
  • MOL 518 Quantitative Methods in Cell and Molecular Biology
  • MSE 504/CHM 560/PHY 512/CBE 520 Monte Carlo and Molecular Dynamics Simulation in Statistical Physics & Materials Science
  • NEU 437/537 Computational Neuroscience
  • NEU 501 Cellular and Circuits Neuroscience
  • NEU 560 Statistical Modeling and Analysis of Neural Data
  • ORF 524 Statistical Theory and Methods
  • PHY 561/2 Biophysics
  • QCB 505/PHY555 Topics in Biophysics and Quantitative Biology
  • QCB 508 Foundations of Statistical Genomics

Biological Courses 

  • CHM 403 Advanced Organic Chemistry
  • CHM/QCB 541 Chemical Biology II
  • EEB 504 Fundamental Concepts in Ecology, Evolution, and Behavior II
  • EEB 507 Recent Research in Population Biology
  • MAE 566 Biomechanics and Biomaterials: From Cells to Organisms 
  • MAE 567/CBE 568 Crowd Control: Understanding and Manipulating Collective Behaviors and Swarm Dynamics
  • MOL 504 Cellular Biochemistry
  • MOL 506 Cell Biology and Development
  • MOL 518 Quantitative Methods in Cell and Molecular Biology
  • MOL 521 Systems Microbiology and Immunology
  • MOL 523 Molecular Basis of Cancer
  • MOL 559 Viruses: Strategy & Tactics
  • QCB 490 Molecular Mechanisms of Longevity 

Selected undergraduate courses of interest
(Note: these do not count towards course requirements)

  • APC 350 Introduction in Differential Equations
  • COS 226 Algorithms and Data Structures
  • EEB 324 Theoretical Ecology
  • MOL/QCB 485 Mathematical Models in Biology
  • ORF/MAT 309/380 Probability and Stochastic Systems
  • QCB 302 Research Topics in QCB  

Additional pre-generals requirements

Research Colloquium: QCB Graduate Colloquium
QCB Graduate Colloquium is a research colloquium that has been developed for QCB graduate students, held weekly on an afternoon during the fall and spring terms. Graduate students have the opportunity to present their research to peers. 

Rotations
All students are required to complete a minimum of three research rotations during their first year of graduate study, with a maximum of four, to explore possible research advisers.

General exam

The general examination is usually taken in January of the second year, and consists of a 7 page written thesis proposal and a 2-hour oral session on the student’s thesis proposal.

Qualifying for the M.A.

The Master of Arts (M.A.) degree is normally an incidental degree on the way to a full Ph.D. and is earned after a student successfully passes the general examination. It may also be awarded to students who, for various reasons, leave the Ph.D. program, provided the student has completed all coursework, pre-generals requirements, and the written portion of the generals examination.

Teaching

A student must teach a minimum of one full-time assignment (6 AI hours), or teach two part-time assignments of 2 or more AI hours each.  Students will typically teach in year 4 of the program.

Post-Generals requirements

Committee Meetings
Research progress is overseen by a thesis committee selected by the student after passing the general exam. The committee consists of the thesis adviser(s) and two additional faculty members. At least one member must be QCB faculty. The thesis committee must be approved by the DGS.

Dissertation and FPO

The dissertation and final public oral exam (FPO) are required for all Ph.D. students. All students must write and successfully defend their dissertation according to Graduate School rules and requirements. 

Faculty

  • Director

    • Ned S. Wingreen
  • Director of Graduate Studies

    • Ned S. Wingreen
  • Executive Committee

    • Brittany Adamson, Molecular Biology
    • Joshua Akey, Integrative Genomics
    • Julien F. Ayroles, Ecology & Evolutionary Biology
    • William Bialek, Physics
    • Michelle M. Chan, Molecular Biology
    • Thomas Gregor, Physics
    • Sarah D. Kocher, Ecology & Evolutionary Biology
    • Michael S. Levine, Molecular Biology
    • Coleen T. Murphy, Molecular Biology
    • Yuri Pritykin, Computer Science
    • Joshua D. Rabinowitz, Chemistry
    • Joshua W. Shaevitz, Physics
    • Stanislav Y. Shvartsman, Chemical and Biological Eng
    • Mona Singh, Computer Science
    • John D. Storey, Integrative Genomics
    • Olga G. Troyanskaya, Computer Science
    • Eric F. Wieschaus, Molecular Biology
    • Ned S. Wingreen, Molecular Biology
    • Martin Helmut Wühr, Molecular Biology
  • Associated Faculty

    • Mohamed S. Abou Donia, Molecular Biology
    • Robert H. Austin, Physics
    • Bonnie L. Bassler, Molecular Biology
    • Clifford P. Brangwynne, Chemical and Biological Eng
    • Mark P. Brynildsen, Chemical and Biological Eng
    • Curtis G. Callan, Physics
    • Daniel J. Cohen, Mechanical & Aerospace Eng
    • Ileana M. Cristea, Molecular Biology
    • Danelle Devenport, Molecular Biology
    • Jianqing Fan, Oper Res and Financial Eng
    • Elizabeth R. Gavis, Molecular Biology
    • Zemer Gitai, Molecular Biology
    • Frederick M. Hughson, Molecular Biology
    • Martin C. Jonikas, Molecular Biology
    • Yibin Kang, Molecular Biology
    • Andrej Kosmrlj, Mechanical & Aerospace Eng
    • Andrew M. Leifer, Physics
    • Simon A. Levin, Ecology & Evolutionary Biology
    • Jonathan M. Levine, Ecology & Evolutionary Biology
    • Lindy McBride, Ecology & Evolutionary Biology
    • Tom Muir, Chemistry
    • Mala Murthy, Princeton Neuroscience Inst
    • Cameron A. Myhrvold, Molecular Biology
    • Celeste M. Nelson, Chemical and Biological Eng
    • Sabine Petry, Molecular Biology
    • Catherine Jensen Peña, Princeton Neuroscience Inst
    • Eszter Posfai, Molecular Biology
    • Ben Raphael, Computer Science
    • Mohammad R. Seyedsayamdost, Chemistry
    • Corina E. Tarnita, Ecology & Evolutionary Biology
    • Jared E. Toettcher, Molecular Biology
    • Samuel S. Wang, Princeton Neuroscience Inst
    • Haw Yang, Chemistry

For a full list of faculty members and fellows please visit the department or program website.