[Comp-neuro] MBL Methods in Computational Neuroscience Course: Applications due March 7

Mark Steven Goldman msgoldman at ucdavis.edu
Sat Feb 25 06:08:40 CET 2017


Applications are open for the Methods in Computational Neuroscience
course at the Marine Biology Laboratory in Woods Hole, MA.  The course
will run from July 30 to August 24, 2017, and the online application
form can be found at:
https://ws2.mbl.edu/studentapp/studentapp.asp?courseid=MCN
The course application deadline is *March 7*.

The course covers a range of topics in computational neuroscience
including neuronal biophysics, neural coding & information processing,
circuit dynamics, learning & memory, motor control, and cognitive
processing & disease.  In addition, numerous tutorials and problem sets
will cover a broad range of computational and mathematical modeling
methods.  The course strongly emphasizes the collaboration between
theory and experiment in solving neuroscience problems, and lectures
will be given by a mixture of theorists and experimentalists.  The
final weeks of the course are primarily reserved for work on
projects that students design in collaboration with the resident
faculty. Further information can be found on the MCN website:
http://www.mbl.edu/mcn/

2017 Course Directors:
Michale Fee, MIT
Mark Goldman, UC Davis

2017 Confirmed Faculty:
Larry Abbott, Columbia University
Steve Baccus, Stanford University
Carlos Brody, Princeton University
Emery Brown, MIT
Dmitri Chklovskii, Simons Foundation
Uri Eden, Boston University
Bard Ermentrout, University of Pittsburgh
Adrienne Fairhall, University of Washington
Ila Fiete, UT Austin
Loren Frank, UCSF
Stefano Fusi, Columbia University
Jack Gallant, UC Berkeley
Surya Ganguli, Stanford University
Nancy Kopell, Boston University
Eve Marder, Brandeis University
Bartlett Mel, University of Southern California
Jonathan Pillow, Princeton University
Cristina Savin, NYU
Terry Sejnowski, Salk Institute
Sara Solla, Northwestern University
Haim Sompolinsky, Hebrew University
Josh Tenenbaum, MIT
Xiao-Jing Wang, NYU

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