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Field
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, reliability, and stochastic simulation concepts with experience in wildfire modeling and loss assessment and regional planning of rural communities. The individual will contribute to the development of solution
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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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NSF, FEMA, DHS, and other local agencies. They will lead research activities involving harnessing and synthesizing the latest developments in artificial intelligence, remote sensing, and simulation and
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simulation models to analyze, predict, and optimize water distribution networks. Engage in state-of-the art research on lithium supply chain dynamics, forecasting potential bottle-necks, and proposing
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, and optimize for energy efficiency HPC applications and high performance data stream analytics workloads. Use of novel accelerator designs, and automatic methods to model/predict how performance would
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and simulation tools, such as spreadsheet-based process cost modeling, input/output modeling, or commercially available life cycle analysis tools such as SimaPro and openLCA. Excellent written and oral
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research, with a particular interest in decision/simulation modeling and cost-effectiveness analysis. The ideal candidate will have strong quantitative skills and an interest in applying modeling
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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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and electronic materials with an emphasis on performance in extreme environments, and workforce development to meet the semiconductor sector needs. We leverage advanced simulation and modeling