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on performance, safety, and robustness of robotic and learning-enabled systems. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear
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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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—such as bent, plateaued, and almost perfect nonlinear (APN) functions—and the design of linear codes with prescribed properties useful for cryptography, including minimal, self-orthogonal, LCD and optimal
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used to approximate these nonlinear terms and accelerate solving such problems, at the cost of some optimality guarantees. The trade-offs between speed and optimality could be investigated as well
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expertise in nonlinear model predictive control. Expertise in numerical optimal control. Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Work independently