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expertise covering mathematics, engineering, computer science and social sciences. We offer excellent working conditions in an international and stimulating environment, along with frequent opportunities
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character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer
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and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection, transaction classification, and
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, transactions, smart-contract events) from public blockchains into research-grade databases Developing statistical, graph, and/or machine learning models to study transaction networks, illicit transaction
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sites. We will subsequently use information theory and (or) wavelet analysis to link this data with environmental variables and identify their principal drivers. Functional forms of LUE-WUE and gc will be
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research problems that matter to both theory and practice Attract funding in cooperation with industry partners Contribute to national, European and international research proposals (e.g., FNR funding
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character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer
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-productive knowledge landscape. This position will contribute to the development of digital and face-to-face methods for public involvement, by shaping the theories, methodologies, and tools that underpin
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
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interdisciplinary character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering