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learning force fields (MLFF) for molecular dynamics simulation of systems sizes ranging from ~1000 to 100.000 atoms while preserving the predictive power of first-principles modeling. Moreover
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) that can benefit either from: (i) continual learning, and (ii) spiking neural networks implemented in neuromorphic processors. Design and develop the machine learning algorithms able to provide a good
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interoperability to advance precision medicine for treatment decisions. To learn more about the CLINNOVA project and its objectives, visit: https://www.uni.lu/fr/news/clinnova-to-launch-precision-medicine-initiative
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the University of Luxemburg, is to develop reliable, efficient, and accurate machine learning force fields (MLFF) for molecular dynamics simulation of systems sizes ranging from ~1000 to 100.000 atoms while
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Education. The University`s core asset is its well-connected world-class academic staff which will attract the most motivated, talented and creative students and young researchers who will learn to enjoy
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who will learn to enjoy taking up challenges and develop into visionary thinkers able to shape society. The Faculty of Law, Economics and Finance offers three Bachelor programmes, four Master programmes
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-en/research-groups/svv This is a fully funded position for 23 months within a large, national research project (INSTRUCT - INtegrated Satellite-TeRrestrial Systems for Ubiquitous Beyond 5G
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and optimization we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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, and learning gains from one school lesson to the next. Specifically, this position will focus on the use of electronic diaries (aka experience sampling) and on the exploitation of the collected micro