Princeton University

Receipt of applications for the first generation of QCN PhD students will open in Winter 2007. These students will start their PhDs in Fall 2008.

Students in QCN will be joining a vigorous community of researchers interested in quantitative approaches to biological programs. This community includes members of QCN as well as a number of very active and close sister programs.

QCN students must complete the requirements for a PhD from the Program in Neuroscience and are expected to in addition take quantitative courses and to conduct their PhD research in quantitative and/or computational neuroscience.

We believe that rigorous training in quantitative and computational methods should be closely intertwined with hands-on training in a broad spectrum of modern experimental approaches. Some of the courses highlighting this approach include:

•  Mol 549 - Laboratory in Neuroscience. In this unique laboratory course, taught in the Spring by Profs. David Tank and Alan Gelperin, students learn through hands-on experience to record neural activity using a broad variety of modern techniques. These techniques include intracellular microelectrode, patch clamp, and optical flourescence recording. No previous neurobiology experience is required.
• Mol 437/537 - Computational Neurobiology and Computing Networks. This course surveys current methods in data analysis and modeling for the neurosciences. It is taught in the Spring, and runs in parallel to Mol 549 - Laboratory in Neuroscience. Mol 437/537 uses example problems taken from the Mol 549, so students taking both courses will apply modern modeling and data analysis methods to data they have obtained themselves. Elementary knowledge of linear algebra, differential equations, probability, and some basic programming ability are required. (See Mol 410/510 below.)
  
• Mol 410/510 - Introduction to Biological Dynamics. This course is taught in the Fall and provides elementary knowledge of linear algebra, differential equations, probability, and some basic programming ability. Students will learn to work extensively with the computing package Matlab. The course is intended to provide a basic grounding in mathematical modeling and data analysis for students who might not have pursued further study in mathematics. No previous programming experience necessary.
• Psy 330 - Introduction to Connectionist Models: Bridging Between Brain and Mind This course will provide an introduction to the use of connectionist models (also known as neural network or parallel distributed processing models) as a tool for exploring how psychological functions are implemented in the brain, and how they go awry in patients with brain damage.

(For full course listings and descriptions, please see the Graduate Training page of the Program in Neuroscience and the  Princeton course catalog)


How to apply.