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variety of simulation and optimization techniques. Key areas of interest may include control theory, robust optimization, or distributed optimization. 2. The second candidate will focus on applied research
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large-language model applications in healthcare systems, systematically identifying ineffective clinical processes, bioinformatics analyses of population health, as well as more conventional outcomes
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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings
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to support affordable, decarbonized, and resilient water supply. The candidate should have strong experience simulating water treatment unit processes (e.g., activated sludge, denitrification, anaerobic
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, mechanical engineering, or related field. Research experience in robot manipulation, robot learning (imitation, reinforcement learning and /or foundation models) and/or robot perception (vision, depth, touch
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experiences. The Fletcher Lab at Stanford University uses computational systems modeling to advance resilient and equitable water resources management for an uncertain future. Current research topics in the lab