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The FACTS project is a successfully funded applied research project developing a new generation of compact, fast thermal sensing devices for demanding industrial and research environments. The work builds on an established platform and focuses on measurable performance gains, traceable...
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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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Models, Generative AI, Federated and Decentralized Learning, Neurosymbolic and Hybrid AI, Self-Supervised and Few-Shot Learning – and their integration into wireless communications and edge computing
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real or simulated industrial scenarios. Is Your profile described below? Are you our future colleague? Apply now! Education • PhD in Computer Science, Telecommunications, or a closely related field
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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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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 Within the Department
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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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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 objective PhD diploma or a letter/information indicating the expected...
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· An environment encouraging curiosity, innovation and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international
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colleague? Apply now! Education • PhD in Computer Science, Telecommunications, or a closely related field. • Solid knowledge of mobile networks and 5G systems, with practical understanding of RAN optimization