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Qualifications: Experience with probabilistic programming frameworks such as PyMC, Stan, NumPyro, or similar. Experience with system dynamics or compartmental modeling — stock-and-flow formulations, feedback
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to accelerate multiscale materials and flow sciences. Major Duties/Responsibilities: Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists
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modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected
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responses to current or imposed environmental conditions. Research may leverage: Laboratory, growth chamber and field experimental data, and/or new measurements to quantify molecular to ecosystem scale