98 high-performance-quantum-computing-"https:"-"https:"-"https:"-"https:" positions in Luxembourg
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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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on neurodegenerative processes and are especially interested in Alzheimer’s and Parkinson’s disease and their contributing factors. The LCSB recruits talented scientists from various disciplines: computer scientists
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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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teaching programmes in medicine, life sciences, nursing, radiography and midwifery. Research at the department integrates basic and translational, molecular and computational approaches with a focus on
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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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on neurodegenerative processes and are especially interested in Alzheimer’s and Parkinson’s disease and their contributing factors. The LCSB recruits talented scientists from various disciplines: computer scientists
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Wilmes at the Luxembourg Centre for Systems Biomedicine (UL) and Rob Finn at EMBL-EBI in the UK, both involved in the identification of VFs through computational biology, as well as Kim Remans at EMBL in
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will reinforce expertise in digital methods in construction, focused on project management. They are expected to: (i) Conduct research in: Construction informatics, BIM, data science, digital twins AI
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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...