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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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years ) Ph.D. in Engineering, Operations, Computer Science, Mathematics or a related field. Knowledge of optimization, power systems operations and planning, electricity markets, issues surrounding
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measurements at the Center for Nanoscale Materials and analysis of these data. The in-situ experiments will be driven by external electric fields and relevant optical stimuli. Although exceptional candidates in
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The Argonne Leadership Computing Facility (ALCF) is dedicated to advancing scientific discoveries and engineering breakthroughs by providing world-class computing facilities in collaboration with
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and processing strategies aimed at achieving high performance, cost-effectiveness, and manufacturability. The selected candidate will leverage the capabilities of the Materials Engineering Research
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engineering, or a related field. Demonstrated expertise in process modeling, process optimization, and technoeconomic analysis. Programming skills in scientific computing languages such as Python and Julia
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Argonne National Laboratory, a U.S. Department of Energy multidisciplinary science and engineering research center, is committed to finding solutions for national priorities, including advancing
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Leadership Computing Facility (ALCF), the Mathematics and Computer Science Division (MCS), the Computational Science Division (CPS), and the Data Science and Learning Division (DSL). The postdoctoral
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modeling tools to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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dynamics (CFD) to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical