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Raphael has years of experience working with human neuroimaging data, computational cognitive models, and Bayesian statistics. Prior to graduate school, he worked as an imaging data analyst in Neuropsychiatry at the Hospital of the University of Pennsylvania. He received his PhD in Psychology from Columbia University in 2018, where his research focused on the dynamics of large-scale cortical networks during reinforcement learning. In his postdoctoral research, he studied neural representations of uncertainty and used deep neural networks to model the human visual system.