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Many-Body Theory , Quantum Information Theory , Theoretical High Energy Physics , Theoretical particle physics Particle Theory Nuclear Theory Quantum Computing / Quantum Computing Quantum Field Theory
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and Applied Sciences Department/Area Electrical Engineering/Computer Engineering/Computer Science Position Description Project Deep learning plays an essential role in the operation of an autonomous
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The National Energy Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher — Scientific Machine Learning (NESAP) to join the Workflow
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equipment, computer resources, and yearly research support. Appointments are for one year with the possibility of renewal pending satisfactory performance and continued funding. Candidates are encouraged
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assessment, and ambulatory behavioral assessments to precisely track brain and cognitive change over short intervals. The program of research seeks to understand individual differences in aging trajectories
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biology and precision medicine and the Department of Pathology at the Dana-Farber Cancer Institute. Prior experience and desire to perform wet-lab research and cell biology focused research and molecular
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Science Acceleration Program (NESAP ). You will join a multidisciplinary team building AI-driven scientific workflows for the upcoming Doudna supercomputer. Doudna will deliver over 10x the performance
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—specifically fine particulate matter, heat, and humidity—in Philadelphia neighborhoods. The fellow will extend existing research in AI- and data-driven modeling of building systems by developing algorithms and
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, using an array of methods including natural language processing and experiments. This is a two-year position (one-year contract renewable based on performance). The primary criterion for acceptance is
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to upload any additional documents to the “other documents” tab as needed. Skills and Knowledge: Experience with molecular simulations and high-performance computing demonstrated by peer-reviewed publications