[Comp-neuro] Doctoral studies in Computational/Theoretical
Neuroscience at New York University
eero at cns.nyu.edu
Tue Oct 29 22:29:38 CET 2013
New York University is home to a thriving interdisciplinary community of researchers using computational and theoretical approaches in neuroscience. We are interested in exceptional PhD candidates with strong quantitative training (e.g., physics, mathematics, engineering) coupled with a clear interest in brain sciences. A full listing of neuroscience-related graduate programs is available at http://neuroscience.nyu.edu, and a listing of computationally-oriented faculty, sorted by their primary departmental affiliation, is given below. Doctoral programs are flexible, allowing students to pursue research across departmental boundaries. Nevertheless, admissions are handled separately by each department, and students interested in pursuing graduate studies should submit an application to the program that best fits their goals and interests.
** Center for Neural Science (CNS) (deadline: 12 December)
[Graduate Studies in Neuroscience across NYU: http://www.neuroscience.nyu.edu/]
* André A. Fenton - Molecular, neural, behavioral, and computational aspects of memory.
* Paul W. Glimcher - Decision-making in humans and animals.
* Roozbeh Kiani - Vision and decision-making.
* Wei Ji Ma (also in Psychology) - Perception, working memory, and decision making.
* Tony Movshon - Vision and visual development.
* Bijan Pesaran - Neuronal dynamics and decision making.
* Alex Reyes - Functional interactions of neurons in a network.
* John Rinzel (also in Mathematics) - Biophysical mechanisms and theory of neural computation.
* Nava Rubin - Visual perception and the neural basis of vision.
* Robert Shapley - Visual physiology and perception.
* Eero Simoncelli - Computational vision.
* Xiao-Jing Wang - Computational neuroscience, decision-making and working memory, neural circuits.
** Psychology, Cognition & Perception program (deadline: 12 December)
* Nathaniel Daw (also in CNS) - Models of decision-making and neuromodulation.
* David Heeger (also in CNS) - fMRI, computational neuroscience, vision, attention.
* Michael Landy - Computational approaches to vision.
* Laurence Maloney - Mathematical approaches to psychology and neuroscience.
* Gary Marcus - Origins of the human mind.
* Denis Pelli - Visual object recognition.
* Jonathan Winawer - Visual perception and memory.
** Mathematics (deadline: 18 December )
* David Cai - Nonlinear stochastic behavior in physical and biological systems.
* David McLaughlin - Nonlinear wave equations, computational visual neuroscience.
* Aaditya Rangan - computational neurobiology, numerical analysis.
* Charles Peskin - Mathematical biology.
* Michael Shelley - Modeling and large-scale computation, computational visual neuroscience.
* Daniel Tranchina - Information processing in the retina.
** Computer Science (deadline: 12 December)
* Davi Geiger - Computational vision and learning.
* Yann LeCun - machine learning, hierarchical visual processing, robotics.
** Electrical and Computer Engineering, Poly campus, Brooklyn (deadline: 1 December)
* Jonathan Viventi - Brain-computer interfaces and brain recording technologies.
** Economics (deadline: 18 December)
* Andrew Caplin - Economic theory, neurobiology of decision.
* Andrew Schotter - Experimental economics, game theory, neurobiology of decision.
More information about the Comp-neuro