124 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions in Luxembourg
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Specialist will be a member of the Department of Geography and Spatial Planning (https://dgeo.uni.lu ), joining the Economic Geography team of Prof. Christian Schulz. The position contributes to the INTERREG
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if they demonstrate strong relevant skills. Coursework or strong background in computational mechanics / FEM, numerical methods, and scientific programming. Exposure to machine learning / data-driven modelling and/or
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
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Intelligence, Computational Linguistics, Data Science, or a closely related field Strong programming skills, e.g., Python, and familiarity with machine learning and/or software engineering workflows; experience
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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
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integrating distributed energy resources, demand response, and storage, this project aims to enhance grid flexibility and increase the use of renewable energy. Where to apply Website https://app.skeeled.com/s
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/admittance, force control Experience with Artificial Intelligence and deep learning concepts for robotics computer vision, tactile sensing, reinforcement learning Experience with robotic simulation tools e.g
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administrations, including eBus Competence Center, Emile Weber, GomSpace, Gradel, IEE, Nexxtlab, Telindus, and Ville de Luxembourg. For more information on the ATLAS IPBG Programme, see here: https://edu.lu/wwpy7
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strong sense of responsibility. Where to apply Website https://www.lih.lu/en/job/?value=JA/PD0226/RK/BIOINFO Requirements Research FieldComputer science » InformaticsEducation LevelPhD or equivalent
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machine learning technologies in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, sustainable agri-food systems