34 computational-physics "https:" "https:" "https:" "https:" "Ulster University" PhD positions in Luxembourg
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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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, Mechanical Engineering, Structural Engineering, or a closely related field. Candidates from Materials Science, Civil Engineering, Physics, Applied Mathematics, or Computational Engineering are welcome
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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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through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about research? So are we! Come
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2027 - 01:48 (UTC) Country Luxembourg Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Mathematics, Physics, Computer Science, Engineering or another quantitative subject are particularly encouraged to apply. Language Requirements: Applicants must demonstrate at least B2-level proficiency in
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citizens in their choices, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute
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11 Dec 2025 Job Information Organisation/Company Luxembourg Institute of Science and Technology Research Field Physics Engineering » Materials engineering Researcher Profile First Stage Researcher
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job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Temporary contract | 14
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular