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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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efficiency will be studied. In addition, the effect of the AOP on the overall water quality (physico-chemical and microbiological) will be evaluated and the potential for optimizing the AOP conditions by
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previously conducted research or have demonstrated knowledge within some of the following areas: classical and/or quantum data communication, error correction, communication algorithms, optimization algorithms
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are carried out in direct collaboration with industry to a great extent. The position is offered in relation to the research program "Power Electronic Control Reliability and System Optimization" and the PhD
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industry to a great extent. The position is offered in relation to the research program "Power Electronic Control Reliability and System Optimization" and the postdocs will be positioned to the section
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security guarantees. Topics include federated learning, secure computation, and robust optimization under adversarial threats. The candidate should have an MSc. in Machine Learning, Computer Science
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, holistic planning and scheduling to optimize resilience across several factory systems. Development of AI-based tools and complex simulation systems is expected to be a core contribution. 3) IT and OT
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The aim of the project is to generate De novo enzymes to degrade PET from composite fibers from recycled textiles. The first-generation designs will be further optimized after experimental
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The aim of the project is to generate De novo enzymes to degrade PET from composite fibers from recycled textiles. The first-generation designs will be further optimized after experimental
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, probability theory, and combinatorial optimization. Experience in decision-making under uncertainty and autonomous system operation. High level written and spoken English skills. You may obtain further