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 28 to August 24, 2022, and the online application form can be found at: https://www.mbl.edu/education/advanced-research-training-courses/course-offe... The course application deadline is *March 30*. 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/ 2022 Course Directors: Stephen Baccus, Stanford University Xiao Jing Wang, New York University 2022 Faculty: Larry Abbott, Columbia University Tim Behrens, Univ. College London Emery Brown, MIT Randy Buckner, Harvard University Anne Churchland, UCLA Claudia Clopath, Imp. College London Albert Compte, IDIBAPS Shaul Druckmann, Stanford University Uri Eden, Boston University Bard Ermentrout, U. of Pittsburgh Adrienne Fairhall, U. of Washington Michale Fee, MIT James Fitzgerald, Janelia Res., HHMI Loren Frank, UCSF Stefano Fusi, Columbia University Surya Ganguli, Stanford University Paul Glimcher, New York University Mark Goldman, UC Davis Nancy Kopell, Boston University Eve Marder, Brandeis University Yiota Poirazi, IMBB-FORTH David Redish, U. Minnesota Terry Sejnowski, Salk Institute Reza Shadmehr, Johns Hopkins Univ. Sara Solla, Northwestern University Haim Sompolinsky, Hebrew University Nelson Spruston, Janelia Res., HHMI Josh Tenenbaum, MIT Nao Uchida, Harvard University Greg Wayne, DeepMind