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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
universities in the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital
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. Experience with high-throughput molecular biology assays. Experience with complex functional experiments. Background in machine learning, AI, or data integration for genomic datasets. Familiarity with gene
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Organization National Energy Technology Laboratory (NETL) Reference Code NETL-Postdoc How to Apply A complete application consists of: An application, including academic history, work history
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for healthcare. The Alsentzer Lab is an interdisciplinary research group in the Department of Biomedical Data Science at Stanford University. Our mission is to leverage machine learning (ML) and natural
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at the intersection of AI/deep learning, bioinformatics, mathematical modeling, computational topology, scientific machine learning, for systems biology, single-cell genomics and protein design. The candidates will
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of executive control, and contextual modulators of executive control like emotion and motivation. We use and develop advanced computational methods, including “big data” statistical methods, machine learning
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based on predictions from statistical and machine learning models Postdoctoral scholars are represented by UAW 4121 and are subject to the collective bargaining agreement, unless agreed exclusion criteria
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processes and artificial intelligence and machine learning methods. The goal of Geophysicist.AI is to develop a scalable artificial intelligence ecosystem that integrates large language and physics-informed
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nano-mechanics, and machine learning as it applies to the field of computational mechanics. Candidates will be given opportunities to develop their teaching experience by designing and teaching a class
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Cancer Registry, as part of the national SEER registries. The postdoc fellow will work closely with statisticians, computer scientists, oncologists, and epidemiologists in the lab and other collaborating