25 developer-"https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions at Université de Montpellier in France
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for developing new molecular biosurveillance tools, transferable to local species, thereby contributing to i) improving the capacity to monitor ecotoxicological hazards and water resource quality, and ii
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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of this brain cancer, as well as the evolution of the tumor. This part of the project involves designing, developping, and running machine learning algorithms and approaches to exploit vectors of RNA modification
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observations disponibles dans les observatoires de l'infrastructure de recherche OZCAR comme l'Observatoire du Larzac (https://deims.org/83b01fa5-747f-47be-9185-408d73a90fb2
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candidate. (1) Develop multisource, frugal downscaling approaches. Most downscaling approaches presented in the scientific literature are Machine Learning (ML)-based. The proposing team's experience is that
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initiation and evolution. Different rheological parameterizations of yield-strength and dislocation creep will be compared in regional and large-scale numerical models of mantle dynamics. We will in particular
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will be to study new examples, study small dimensions, and develop an equivariant perspective on toric degenerations