340 machine-learning "https:" "https:" "https:" Postdoctoral positions in United States
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
characteristics, drug efficacy, and safety profiles, and how these relationships can be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2
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this position will work as a member of an interdisciplinary team on research involving the use of statistical and machine learning methods for the development of Immune Digital Twins. There will be
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position will work as a member of an interdisciplinary team led by Dr. Colin Xu on Department of Defense (DoD)-funded research project involving the use of statistical and machine learning methods for
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large‑scale systems neuroscience with machine learning to derive principled models of cortical computation. Our newly refurbished primate facility, state‑of‑the‑art Neuropixels rigs, and high
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performance utilizing a variety of tools including life-cycle assessment (LCA), machine learning techniques, and/or optimization methods. This position will carry out state of the art research into the
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geometry, number theory, data. * Qin Li: Scientific computing, machine learning, inverse problems. * Hanbaek Lyu: Combinatorics, probability, optimization, and machine learning. * Laurentiu Maxim
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information from multimodal spatiotemporal data, including physiological signals, imagery, and natural language, via adaptive machine learning; 2) Personalization of sequential decision making
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integrated modeling and machine learning for energy and circular-economy applications. The Post Doctoral Associate will design and execute simulation and machine-learning studies, analyze results
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, audited, and trusted. The appointed researcher will publish in top venues in artificial intelligence, machine learning, and operations research; contribute to open-source releases; and work closely
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Carlo, GW, and other advanced techniques are oftentimes needed to correctly describe correlated electronic systems. In recent years, electronic structure methods have been coupled to machine learning