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candidates in the general area of machine learning and radio resource allocation for emerging wireless networks within its Signal Processing and Communications (SIGCOM) research group. SnT carries out
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position within a Research Infrastructure? No Offer Description Are you interested in building state-of-the-art machine learning systems for the most complex, and fastest growing, transportation network in
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. Here's what awaits you at SnT A stimulating learning environment. Here post-docs and professors outnumber PhD students. That translates into access and close collaborations with some of the brightest ICT
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learning force fields (MLFF) for molecular dynamics simulation of systems sizes ranging from ~1000 to 100.000 atoms while preserving the predictive power of first-principles modeling. Moreover
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) that can benefit either from: (i) continual learning, and (ii) spiking neural networks implemented in neuromorphic processors. Design and develop the machine learning algorithms able to provide a good
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the University of Luxemburg, is to develop reliable, efficient, and accurate machine learning force fields (MLFF) for molecular dynamics simulation of systems sizes ranging from ~1000 to 100.000 atoms while
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interoperability to advance precision medicine for treatment decisions. To learn more about the CLINNOVA project and its objectives, visit: https://www.uni.lu/fr/news/clinnova-to-launch-precision-medicine-initiative
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The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The University was founded in 2003 and counts more than 6,700 students and more than 2,000 employees from around the world. The University’s faculties and...
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The junior group in Imaging AI develops applied AI research focused on biomedical signal analysis and medical image computing. The general aim of the group is translating bleeding edge algorithms from fundamental AI and imaging research closer to a concrete biomedical application. We are looking...
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The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from highly motivated PhD candidates in the general area of machine learning and radio resource allocation