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, industrial and international partners. SnT is active in several national projects funded by National Research Fund (FNR) and local industries, and international research projects funded by the EU FP7 program
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technologies (fiber-optic sensors, DIC), and computer science (machine learning tools) in collaboration with de department of Physics. The aim of the BriCE project is to develop a novel bridge monitoring
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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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Sensor Fusion: Strong background in processing and fusing data from cameras, LiDAR, radar, or other sensors for robust autonomous system perception ML Engineering and Experimentation: Proficiency with
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22 Jan 2026 Job Information Organisation/Company Luxembourg Institute of Science and Technology Research Field Environmental science Researcher Profile First Stage Researcher (R1) Positions Postdoc
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2 Feb 2026 Job Information Organisation/Company University of Luxembourg Research Field Educational sciences » Education Researcher Profile Recognised Researcher (R2) Application Deadline 26 Jan
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2 Feb 2026 Job Information Organisation/Company University of Luxembourg Research Field Educational sciences » Other Researcher Profile Recognised Researcher (R2) Application Deadline 30 Dec 2026
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2 Feb 2026 Job Information Organisation/Company University of Luxembourg Research Field Educational sciences » Education Researcher Profile Recognised Researcher (R2) Application Deadline 15 Jan
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The successful candidate is expected to take a leading role in defining, acquiring, managing, and scientifically contributing to projects around AI-enabled space-borne perception systems for robotic proximity operations in collaboration with Redwire Space Luxembourg. The candidate will carry a...
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We invite applications for a postdoctoral researcher to join the UMLFF project at the University of Luxembourg. The project aims to develop the next generation of uncertainty-aware machine-learning force fields (MLFFs) that combine state-of-the-art equivariant neural network architectures with...