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and machine-learning methods for rapid surrogate modeling, model calibration, state estimation, uncertainty quantification, and physics-informed prediction. Contribute to U.S. Department of Energy
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system surrogates, or uncertainty quantification. Model Predictive Control (MPC), data-driven control, or hybrid model-based / data-driven controller synthesis (e.g., RL-MPC) for complex dynamical systems
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our complex society. Dr. String’s lab profile at Gabrielle String and Dr. McAndrew’s lab profile at Computational Uncertainty Lab Other responsibilities may include: Design, execute, and analyze
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