The Graduate Program in Computational Neuroscience
The University of Chicago has a long tradition of innovative research in the neurosciences. K. C. Cole developed the voltage clamp here, Stephen Polyak and C. J. Herrick did pioneering work on the anatomy of the retina and brain, and Jack Cowan and Hugh Wilson were among the first to develop mathematical analyses of the dynamics of cortical neurons using non-linear dynamics. This tradition is continued in The Committee on Computational Neuroscience, which provides an interdepartmental and interdivisional focus for multidisciplinary training in neuroscience.
Computational neuroscience is a relatively new area of inquiry that is concerned with how components of animal and human nervous systems interact to produce behaviors. It relies on quantitative and modeling methods to understand the function of the nervous system, natural behaviors and cognitive processes, and to design human-made devices that duplicate behaviors. Course work in computational neuroscience can prepare students for research in neurobiology, psychology, or in the mathematical or engineering sciences. Graduates from this program move to traditional academic careers, to careers in biomedical research or engineering, or to opportunities in the corporate world.
For more information regarding the graduate program in Computational Neuroscience, please read the CNS student handbook.
If you have any questions regarding admissions to this program, please email email@example.com.