The Center for Computational Neuroscience (CCN) aims to develop theories, models, and computational methods that deepen our knowledge of brain function. CCN takes a “systems” neuroscience approach, building models that are motivated by fundamental principles, that are constrained by properties of neural circuits and responses, and that provide insights into perception, cognition and behavior. This cross-disciplinary approach not only leads to the design of new model-driven scientific experiments, but also encapsulates current functional descriptions of the brain that can spur the development of new engineered computational systems, especially in the realm of machine learning. CCN is one of five centers that make up the Flatiron Institute, an internal scientific unit of the Simons Foundation, focused on computational aspects of a wide range of basic science. The overall mission of the Flatiron Institute is to advance scientific research through computational methods, including theory, modeling, simulation and data analysis.
Learn MoreApplications are invited for postdoctoral Flatiron Research Fellowships (FRFs) at the Center for Computational Neuroscience (CCN) within the Flatiron Institute at the Simons Foundation. CCN’s research groups include:
● Computational vision (PI: Eero Simoncelli)
● Neural circuits and algorithms (PI: Dmitri ‘Mitya’ Chklovskii)
● Statistical analysis of neural data (PI: Alex Williams)
The mission of CCN is to develop theories, models, and computational methods that deepen our knowledge of brain function. CCN takes a vertically-integrated “systems” neuroscience approach, building models that are motivated by fundamental principles, that are constrained by properties of neural circuits and responses, and that provide insights into perception, cognition and behavior. This cross-disciplinary approach not only leads to the design of new model-driven scientific experiments, but also encapsulates current functional descriptions of the brain that can spur the development of new engineered computational systems, especially in the realm of machine learning.