45 machine-learning "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" "Mines Paris PSL" Postdoctoral positions in Luxembourg
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curiosity, innovation and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international work environment with
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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-performance computing resources suitable for large-scale machine-learning and foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025
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SD-26083 – POSTDOCTORAL RESEARCHER IN THE CHEMICAL VAPOR DEPOSITION OF METAL ORGANIC FRAMEWORKS F...
: https://www.list.lu/ How will you contribute? The CLEANH3 project investigates the gas phase synthesis of metal organic frameworks for the conversion of small and low-energy molecules into advanced
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SD-26084 – POSTDOCTORAL RESEARCHER IN THE CHEMICAL VAPOR DEPOSITION OF COVALENT ORGANIC FRAMEWORK...
: https://www.list.lu/ How will you contribute? The CLEANH3 project investigates the gas phase synthesis of covalent organic frameworks for the conversion of small and low-energy molecules into advanced
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities and Machine Learning/AI on organisations from both the private and public sectors
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/performance trade-offs and typical RAN levers; experience with energy metering data is a plus. • Strong background in AI / Machine Learning for decision-making (e.g., forecasting, optimization with learning
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our website: https://www.list.lu/ How will you contribute? As part of a major European project on high‑performance, multifunctional textile materials, the Luxembourg Institute of Science and Technology
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training covering topics such as computational modelling, numerical methods, statistical analysis, machine learning or data-driven analysis of complex systems Experience 0–3 years of postdoctoral experience