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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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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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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
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scientific conferences and publish models and scientific insights in high-impact journals Who You Are: Ph.D. in Computational Biology, Bioinformatics, Computer Science or Machine Learning related field
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datasets, performing statistical analyses and machine learning approaches to identify biomarkers of treatment responses. The candidate will also develop and implement bioinformatics pipelines in a high
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a collaborative and demanding one to two year leadership program designed to provide a unique development opportunity for recent graduates of MHA, MBA, MPH and other programs as they start their
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Administration, or an equivalent degree program. Applicants must have earned their degree prior to starting the program, except for programs that require a Residency or Fellowship Prior work experience in
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growth for Portland, Maine, and northern New England. We are nurturing an environment for high-impact research and innovation in computer and data science, digital engineering, the advanced life sciences