339 structural-engineering "https:" "https:" "https:" "https:" "UCL" "UCL" positions at CNRS in France
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contributes to tools such as ProVerif and Tamarin. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7503-VERCOR-005/Candidater.aspx Requirements Research FieldComputer scienceEducation LevelPhD
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proposed by FLI and ALPAO will make it possible to tackle both the problem of speed, and that of spatial scaling in anticipation of the ELT. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre
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scientists working in diverse domains of fundamental and applied Physics. The postdoc will integrate the Condensed Matter group at CPHT. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7644
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to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR7261-AICBEL-047/Default.aspx Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Research FieldEnvironmental
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• Openness to interdisciplinary research (climate and social sciences) • Good level of scientific English Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UAR636-ALERUB-040/Default.aspx
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, fluid, and gas transfers on the formation of resources such as natural hydrogen. This issue will be re-evaluated in the Aquitaine Basin and the northern Pyrenees. Where to apply Website https
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encoding of information, inspired by concepts from single-pixel imaging, and transposed to fluorescence microscopy through the use of structured illumination with variable frequency. The objective is to
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31 Jan 2026 Job Information Organisation/Company CNRS Department Laboratoire des Sciences des Procédés et des Matériaux Research Field Engineering Physics Technology Researcher Profile Recognised
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ecosystems, with close links to several major European initiatives and partnerships with leading technology providers. A strong and lasting impact is built-in through a two-tier exploitation strategy
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AI researchers from ANITI, IMT and CERFACS, as well as with researchers/engineers in weather forecastings from the CNRM (Météo-France). Hybridization methods between neural networks and physical models