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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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Wetsus - European centre of excellence for sustainable water technology | Netherlands | about 1 month ago
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
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, these models often use simplified, linearized assumptions, limiting their capacity to capture the nonlinear complexities inherent in real-world hydrological processes. Recently, there has also been the branch
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scales and different phases which leads to nonlinear time and history dependent material behavior. Additionally, innovative changes are happening in the steel production process, especially in the drive
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to: - Developing underwater communication systems using deep learning which are well-performing to nonlinear channels. - Establishing a deep learning architecture which is optimal for underwater acoustic