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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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, the post-doctoral fellow will consider designing distributed learning algorithms for streaming manifold-valued data. Experiments will be carried out on urban, coastal, and underwater DAS data. The novelty
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. Processing this response provides estimates of the local variations in acoustic pressure along the fiber, over distances ranging from 40km up to 140km with some systems. This technique, called Distributed
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academic and professional qualifications Proven research experience in the field of modelling and analysis of biological networks Solid foundation in mathematics and algorithmic design Strong programming
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About the LCSB The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Luxembourg Centre for Systems Biomedicine (LCSB) is an interdisciplinary research centre of the University of Luxembourg. We conduct...
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About the LCSB The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Luxembourg Centre for Systems Biomedicine (LCSB) is an interdisciplinary research centre of the University of Luxembourg. We conduct...
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for competitive fellowships during their first year with us. The ideal candidate will be recruited by summer 2025. We are particularly seeking postdoc candidates who have recently completed their PhD with a
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learning community. Basically, once the observed data is identified with a probability distribution (possibly the empirical mass function), optimal transport allows to consistently assess the similarity
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frameworks, as they impose minimal, if any, assumptions about the underlying data distribution, making them more effective for detecting a wide range of changes. The CPD algorithms will be designed
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. The monitoring of telecommunications and energy production and distribution networks are characteristic examples of such time-critical applications. The project aims to propose unsupervised online CPD algorithms