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Applications should include: Curriculum Vitae Cover letter detailing your motivation for applying to the advertised research topic and/or project, including how your background, interests, and career goals align with its objectives Transcript of all modules and results from university-level...
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and Management of the Faculty of Law, Economics and Finance of the University of Luxembourg is looking for a Postdoctoral researcher to conduct research in development economics. The postdoctoral
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supported by COMMLab, 6GSPACE Lab, HybridNetLab, QCILab, TelecomAI Lab, CSAT Lab, our SW Simulators, and our Facilities. For further information, you may refer to https://www.uni.lu/snt-en/research-groups
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with the disciplinary approach a very ambitious interdisciplinary research culture has been developed. The faculty’s research and teaching focuses on social, economic, political and educational issues
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effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural networks (GNNs) to accelerate
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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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research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we live in
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with the disciplinary approach a very ambitious interdisciplinary research culture has been developed. The faculty’s research and teaching focuses on social, economic, political and educational issues
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to global citizenship education (GCE) that can support children in developing knowledges, skills and attitudes for building a more inclusive, peaceful and sustainable future. CHANGES seeks to advance GCE
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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