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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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research lines. Research line 1: "Digital twinning for 3D network optimization" focuses on developing distributed digital twin architectures and mechanisms for distributed network optimization in networks
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conflict. This may involve formation control, adaptive trajectory planning, and real-time vehicle communication to avoid interference and optimize coverage. Control techniques and sensor fusion will be
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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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integrated, 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
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processing, optimization, or information theory; Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid, is a plus; Familiarity with the basic concepts