697 parallel-computing-numerical-methods-"Simons-Foundation" positions at Stanford University
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training. Oversee the planning, execution and integration of initiatives and activities related to SMCI operations and goals. Lead and/or collaborate in program management of SMCI operations including
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the theories and methods of a life science discipline to interpret and perform analyses of experiment results; offer suggestions regarding modifications to procedures and protocols in collaboration with senior
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including statistical software, and evaluation of methods. Stanford University is one of the world’s most renowned universities. Sitting in the heart of the San Francisco Bay Area among the valley’s most
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will have the opportunity to test, develop, and implement the innovative sample preparation methods required to keep Stanford researchers on the cutting-edge. The successful candidate will also have the
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students in H&S engage in inspirational teaching, learning, and research every day. Department/Program Description: Big Local News, situated in the journalism program in the Department of Communication
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outcomes. Apply the theories and methods of a life science discipline to interpret and perform analyses of experiment results; offer suggestions regarding modifications to procedures and protocols in
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the major functions of a large warehouse. The position, selects, determines, and apply storekeeping guides, procedures, and methods without specific instructions from supervisors. Stanford Auxiliary
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advanced statistical methods (e.g., hierarchical linear modeling) a plus. Experience working with K-12 or postsecondary education data a plus. PHYSICAL REQUIREMENTS*: Constantly perform desk-based computer
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the future. Together, faculty and students in H&S engage in inspirational teaching, learning, and research every day. Department/Program Description: Big Local News, situated in the journalism program in
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genomics datasets for model training in computers. Independently conduct experiments; maintain detailed records of experiments and outcomes; run training and inference of AI models for cancer diagnosis