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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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that ingest raw on-chain data (blocks, transactions, smart-contract events) from public blockchains into research-grade databases Developing statistical, graph, and/or machine learning models to study
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Computer Science, Information Theory, Physics or related fields High level of mathematical maturity Experience with topics related to quantum LDPC codes and decoding algorithms, or demonstrated ability and
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Control / Estimation Theory Intermediate programming skills in Python and C++ Intermediate level skills and proven experience with PyTorch Working knowledge of ROS and previous experience of handling
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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, Machine Learning, Physics, Mathematics, Engineering, or equivalent A solid publication record with research publication(s) in peer-reviewed international journals Good programming skills (ideally in Python