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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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industry’s biggest challenges: Closed-Loop Design and Optimization of Biologics. The research program will build on the recent advances in protein design, automation, and multi-parameter optimization and
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on generating new knowledge for optimizing biological conversion of carbon dioxide to acetic acid in close collaboration with an industrial end-user of the developed technology. Responsibilities and tasks Your
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during training, an effect attributed to the properties of the optimization technique. Intuitively, stochastic optimizers tend to converge to flatter minima in the complex loss landscape, which is believed
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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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objective is to surpass the current traditional thermodynamic and optimization approaches, which are constrained in design discovery capabilities and long-term TES performance evaluation. Through your
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, Electrical Engineering, Mathematics, Control theory, Cyber-physical systems, or any other related discipline, potentially with skills in Power Electronics. Applicants who are in the final phase