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. CCN's research groups include: Computational vision (PI: Eero Simoncelli) Neural circuits and algorithms (PI: Dmitri ‘Mitya' Chklovskii) NeuroAI and geometric data analysis (PI: SueYeon Chung) Statistical analysis of neural data (PI: Alex Williams) CCN also has an open source software development group, and interns may choose to work with this group, in coordination with one of the research groups listed above.
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Career Level
Intern
Education Level
Bachelor's degree