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Description In this project we will extract affordable potentials from expensive DFT results through machine learning (ML) to accelerate nanomaterial growth in MD simulations. Such interactomic potentials
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-based multi-agent perception and mapping in static and dynamic environments Quantum Machine Learning for robots -Learning and reasoning-based navigation -Distributed intelligence for swarms of robots 6G
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quantified, and machine learning will be used. Duties As a PhD student you are expected to perform both experimental and theoretical work within your research studies as well as communicate your results
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