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Scientific Machine Learning. The successful candidate will develop and deploy state-of-the-art SciML algorithms in high-performance computational physics codes. We accept applications from all candidates with
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research involving biological data analysis and modeling of biological systems. In particular, they will develop and apply algorithms to construct discrete dynamic models of signal transduction networks
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occupant harm from exposure to indoor bioaerosols. Key Responsibilities Responsibilities include, but are not limited to: Developing and analyzing new HVAC control algorithms to balance energy efficiency and
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of the following: quantum field theory, quantum information, out-of-equilibrium dynamics, theoretical cosmology, particle physics, gravity, or quantum algorithms. Candidates are expected to demonstrate
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Sriperumbudur. Potential research projects include (but are not limited to) developing theory and methods for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows
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investigate AI/ML algorithms to deliver behavioral interventions at the moments of need and how those can/should be modified to account for personalized preferences. To accomplish this goal, we study behavior
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the brain. We are particularly looking for a PhD level systems neuroscientist with expertise in animal behavior tracking using deep learning algorithms and its causal link with specific neural circuits
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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