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2027 - 11:23 (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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22 Apr 2026 Job Information Organisation/Company Luxembourg Institute of Science and Technology Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions Postdoc
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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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
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The Department of Finance at the University of Luxembourg invites students to apply for Doctoral researcher positions in Finance. The program follows the standard international format with rigorous
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, Financial Technology (Fintech), Energy Informatics, Energy Economics, and Consumer & Behavioural Research. In particular, they will be integrated into a larger research team and collaborate with team members
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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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) 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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We offer a fully funded PhD student position within the Trustworthy Software Engineering (TruX) Research Group headed by Prof. Dr. Tegawendé F. Bissyandé. The position is embedded in a broader research agenda on trustworthy, data-driven software engineering and AI-assisted development. The...
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We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training costs and energy requirements of state-of-the-art deep learning models significantly, while...