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Field
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their efforts on the education of students and the performance of life-changing research across a wide range of disciplines including medicine, engineering, physical sciences, energy, computer science, and social
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analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section of the Computer Science and Mathematics (CSM) Division. CSM
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facilities. These extended laboratory opportunities, located as part of the University's fam complex, help to further enhance research capabilities and practical demonstrations for agricultural activities
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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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applying advanced computational and experimental approaches to address complex environmental and infrastructure challenges. The postdoc’s work directly supports high-impact research outcomes, student
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systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job
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limited to artificial intelligence, computing theory (algorithms, complexity), data science, statistics, discrete mathematics (graph theory, combinatorics), game theory, machine learning, optimization
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presence of complex landscape elements (lakes, forests, and wetlands) that typify the upper Midwest, this project will be focused on the Marcell Experimental Forest (MEF) in north, central Minnesota. The MEF
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neuroethology and robotics. This position focuses primarily on the neuroethology aspects of our research program, with particular emphasis on understanding the behavioral and neural mechanisms underlying active
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, Outpatient, Carrier, TAF). Develop reproducible code and workflows for data cleaning, linkage, and analysis within Stanford’s secure computing environment. Collaborate with multidisciplinary teams