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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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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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Identifying and validating models for complex structures featuring nonlinearity remains a cutting-edge challenge in structural dynamics, with applications spanning civil structures, microelectronics
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control systems. It will address practical limitations that prevent reaching theoretical performance, with particular emphasis on optimal feedback design, actuator optimization, and novel control strategies
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Work Activities We
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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
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, optimization, and artificial intelligence, with potential applications in energy systems, and infrastructure networks. The successful candidate will become part of a dynamic and internationally connected
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Research Infrastructure? No Offer Description Topic background A proper functioning drinking water distribution network is of major importance for society and keeping this network optimally operational is
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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based