Lewis-Sigler Institute


      Kruglyak group graduate student Joshua Bloom receives NSF Graduate Fellowship 

The turn of the 21st century marks a watershed in the progress of the biological sciences. Biology is being transformed from a largely descriptive activity into a quantitative science whose insights are organically connected to the physical and information sciences.

The Program in Quantitative and Computational Biology at Princeton provides multidisciplinary graduate education under the leadership of the Lewis-Sigler Institute for Integrative Genomics.

The program is meant to include, among others, the fields of genomics, biophysics, computational neurobiology, systems biology, population biology and quantitative genetics, molecular evolution, computational biology, and microbial interactions, all of which are already of interest to faculty in the collaborating departments and the Institute.

QCB currently includes five actively participating departments: Chemistry, Computer Science, Ecology and Evolutionary Biology, Molecular Biology and Physics. A total of 70 faculty representing 12 departments have joined the QCB program.

Ph.D. degrees will be offered by the collaborating academic departments with some indication of the interdisciplinary nature of the thesis.

Information about the undergraduate certificate program in QCB, which is distinct from this graduate program, can be found here.

Prospective students should apply to one of the participating departments, through the office of Graduate Admissions at www.gradschool.princeton.edu/admission.
On the application form, at Page 2, be sure to use the dropdown boxes under "Area of Interest" to indicate your interest in this program.

If you are interested in QCB but unsure which department is most appropriate, please contact us at for advice.

Application Deadlines:
Information about deadlines is found at
www.gradschool.princeton.edu/admission/
applicants/guide/schedule
.


Executive Committee:
(All Executive Committee
members are also Core Faculty.)
Leonid Kruglyak, Chair
William Bialek
Hilary Coller
Simon Levin
Joshua Rabinowitz
Joshua Shaevitz
Stanislav Shvartsman
Mona Singh
John Storey
Olga Troyanskaya
Ned Wingreen

Core Faculty:
Peter Andolfatto
Bonnie Bassler
David Botstein
James Broach
Curtis Callan
Iain Couzin
Edward Cox
Zemer Gitai
Thomas Gregor
John Groves
Michael Hecht
John Hopfield
Laura Landweber
Manuel Llinás
Coleen Murphy
David Stern
David Tank
Saeed Tavazoie
Ron Weiss
Eric Wieschaus
(List all faculty)


Seminars

Students are encouraged to attend the weekly Quantitative and Computational Biology Seminars, and to have lunch in a small QCB discussion group with speakers whose research is of special interest. Students are also encouraged to attend the weekly Postdoc and Fellows Seminars.

Teaching Opportunities

Lewis-Sigler faculty and fellows have developed a new introductory undergraduate Integrated Science curriculum. QCB graduate students will be encouraged to teach in this exciting new program, alleviating the teaching requirements in their home department.

Summer Program

We are developing an exciting new summer course for incoming students that will offer an opportunity to participate in hands-on experiments and learn the basics of theoretical and computational approaches to biology.

Courses and Curriculum

Given the diversity of the participating departments, there is no required "core curriculum." Each department has developed a course of study appropriate for QCB students. There are already many diverse and multi-disciplinary courses available to QCB students and we are adding new courses in the area of genomics and bioinformatics.



the institute: Overview, Donors, News, Scientific Program, and more.

faculty, fellows and staff: Faculty, Lewis-Sigler Fellows, Postdocs, Staff, Recruitment, and more.

education: Undergraduate, Graduate, and more.

resources: Princeton University Microarray Database (PUMAdb), Microarray Facility, and more.

seminars: Lewis-Sigler Institute, Affiliated Departments, Princeton University, and more.

center for quantitative biology

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