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), sensing technologies (fiber-optic sensors, DIC), and computer science (machine learning tools). The aim of this Ph.D. project is to develop a novel bridge monitoring technique based on CLCE coating
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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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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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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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include Post Luxembourg (https://www.post.lu/) and Ohmio Europe (https://ohmio.com/). More information on the 5G Bridges programme can be found here: https://www.fnr.lu/results-5g-bridges-call/ This PhD
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future colleague? Apply now! You hold PhD degree in Materials Science or related discipline. You have experimental experience with ferroelectric (pyroelectric) materials and/or (photo)catalytic water
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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