21 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "https:" "CNRS " PhD research jobs in Luxembourg
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) 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 of teaching and
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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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3 Dec 2025 Job Information Organisation/Company Luxembourg Institute of Science and Technology Research Field Engineering Researcher Profile First Stage Researcher (R1) Recognised Researcher (R2
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Fixed term contract | Belvaux | 12 Months Are you passionate about research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology
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Temporary contract | 24 months | Belval Are you passionate about research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology
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) 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 of teaching and
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usual way of working and the language of communication is English. Our current team members are spread across three universities (University of Luxembourg, Eindhoven University of Technology, and
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within the project AI4TECS Writing a doctoral dissertation in computer science Publishing research findings in leading international conferences and high‑impact journals in AI, machine learning, and
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group with broad research competences and interests, with expertise covering mathematics, engineering, computer science and social sciences. We offer excellent working conditions in an international and
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research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural Networks for MLFFs Implement and test uncertainty-aware