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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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a closely related field. A strong background in quantum mechanics, solid-state physics, and computational modeling. Previous experience with density functional theory or many-body physics (beneficial
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release on these projects can be found at the following link . This position’s focus is on developing engineered systems and methods to quantify the physical interactions between migrating cancer cells and
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