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, lead large-scale benchmarking across the full stack, and develop scalable classical simulations (e.g., tensor networks)—including performance bounds beyond brute-force classical simulability. This role
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and teaching, and are funded by the department’s NSF supported “Southern California Geometry and Topology Center.” Outstanding candidates in all areas of (algebraic, complex, differential) geometry and
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components from MEA devices. Apply fundamental principles to approach and address complex behaviors of MEA devices. Perform multi-physics simulation and modeling for water and CO2 electrolyzers. Work
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research focuses on a geometric understanding of training in deep neural networks. The position offers excellent training opportunities at the intersection of machine learning and applied mathematics
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, under the joint supervision of Prof. Alex Cloninger and Prof. Gal Mishne at UC San Diego. This NSF-funded research focuses on a geometric understanding of training in deep neural networks. The position