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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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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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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors
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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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of at least one high-level programming language (e.g. Java, C/C++) and one scripting language (e.g. Perl, Python) Knowledge of Linux/Unix Knowledge of quantum networking, data mining, machine learning
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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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research and information systems engineering. The group conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, Machine Learning/AI, and IoT/5G
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Alzheimer's and Parkinson's disease and their contributing factors. The LCSB recruits talented scientists from various disciplines. Computer scientists, mathematicians, biologists, chemists, engineers
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... The expected PhD candidate should have: A Computer Science background Expertise in Machine Learning, Deep Learning Good programming skills (python, Java…) Fluent written and verbal communication skills in
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with non-terrestrial networks (NTNs) is considered a plus but it is not required Solid background on mathematical optimization tools Good knowledge of the recent trends in machine learning design