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for building envelopes of new construction and retrofits to enable DOE’s energy efficiency goals. Our synergistic research areas include building science, material and system development, and advanced
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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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preparation of well-characterized target compounds. Apply a range of analytical and characterization techniques to evaluate chelator structure, affinity, selectivity, and metal complexation, including radio-TLC
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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