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methods, stochastic control processes, dynamic programming, deep reinforcement learning. Strong track record in scientific contributions supported by peer-reviewed publications. Strong programming skills
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for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine
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calculations Materials modeling/electronic structure calculations Machine Learning/Deep Learning techniques. Education and Experience: A PhD in physics, astronomy, or a closely related field must be completed
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