1,943 computer-algorithm-"TIMES-HIGHER-EDUCATION" Postdoctoral positions in United States
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algorithms for advanced and multi-modality imaging. Work on system designs, physics models, computation, benchtop experiments with small animals, and clinical translation. Additional areas of interest are in
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the complexities of the human regulome through advanced cell-free DNA profiling and developing cutting-edge computational algorithms and molecular profiling techniques. Our research focuses on early cancer detection
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through the Stanford Impact Labs Postdoctoral Fellowship Program (link is external) with Profs. Irene Lo, Itai Ashlagi, and the Stanford Impact Lab on Equitable Access to Education Postdoctoral Fellow
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driven individual with a PhD in data science, computer science, biomedical informatics, or a similar background with some experience working with large datasets. Prior experience with healthcare is not
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University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA
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computational models and systems using algorithms and analytics for materials and related physical sciences for a broad range of energy, transportation, and advanced manufacturing applications. Major Duties
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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also ranks in the top tier of the WSJ/Times Higher Education World University Rankings and the New York Times’ “Top Colleges for Economic Diversity.” Since 2009, nearly $1 billion has been has invested
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optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise
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not required as part of this position. Required Qualifications: Strong mathematical background, including expertise in one or more of the following areas: machine learning, statistics, and algorithms