229 evolution "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" research jobs at CNRS in France
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rely on the development of models integrating different data sources, initially based on data simulations, consistent with the data sets that are actually available or planned for acquisition, as
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. The work will be primarily computational, focusing on the development of deep neural network model architectures and their training. It will involve extending the preliminary results we have already obtained
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the framework of the PEPR Sous-Sol project ORGMET conducted by a consortium of four French laboratories GET, INEEL/ESRF, LFCR and IPREM (https://www.soussol-bien-commun.fr/fr/appel-projets-2024/orgmet
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((TERAhertz high-sensitivity thermoelectric detector for SENSing and imaging) contract. Absorbing metasurface is a key device of the thermoelectric detector. Where to apply Website https://emploi.cnrs.fr/Offres
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to communicate effectively and work in a team. • Enthusiasm for studying virus evolution. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UPR9022-BENSTE-057/Default.aspx Work Location(s
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description: We are seeking a postdoctoral researcher with solid expertise in device physics modelling, compact model development, and/or circuit simulation. The successful candidate will: • Develop physical
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) is required. More generally, we are looking for an open-minded candidate with an interest in the ecology and evolution of emerging pathogens. Website for additional job details https://emploi.cnrs.fr
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conditions such as cancer, yet the underlying mechanisms remain poorly understood. Understanding how disruptions in these processes contribute to cancer development and cell fate decisions is a central
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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures
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, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical composition and atomistic modeling