333 machine-learning "https:" "https:" "https:" "https:" "U.S" research jobs at Nature Careers
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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Postdoctoral Research Scholar in Machine Learning and Computational Genomics Department of Epidemiology, School of Public Health, University of Pittsburgh The Department of Epidemiology
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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or machine learning, proficiency in deep learning techniques (CNN, VIT, diffusion, GAN) Good understanding of the mathematical foundations of machine learning Mastering python and related AI software
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interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
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an expected PhD by September 1, 2026, who meets the eligibility criteria is welcome to apply. Fellowships are open to any U.S. citizen or permanent resident (Green Card holder) and to non-U.S
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-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating environment due to an active in-house workshop
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A postdoctoral fellow position is available at the Icahn School of Medicine at Mount Sinai, New York, at the laboratory of Dr. Eirini Papapetrou https://labs.icahn.mssm.edu/papapetroulab/ and the
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test therapeutic strategies relevant to understanding and treating pediatric neurological disease. [ https://www.stjude.org/research/initiatives/pediatric-translational-neuroscience-initiative.html
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profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning