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analysis of in situ measurement data and spatial remote sensing data - Participation in the scientific supervision of students - Participation in national and international mobility programs The project is
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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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of ASICs dedicated to the readout of AC-LGAD (Alternating Current coupled Low-Gain Avalanche Diode) sensors, capable of very good timing (~30 ps) and spatial (~20 um) resolutions, which will be exploited by
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for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5126-EMIBAS-021/Default.aspx Work Location(s) Number of offers available1Company/InstituteCentre d'études spatiales de la
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the framework of the ANR EmergeNS whose aim is to understand, through mathematical and computer models, the role that autocatalysis, multistability and spatial heterogeneity may have played in the emergence
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11 Nov 2025 Job Information Organisation/Company CNRS Department Laboratoire d'Etudes en Géophysique et Océanographie Spatiales Research Field Environmental science Environmental science » Earth
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, Besançon). Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR6049-JEAFOL-001/Candidater.aspx Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Research
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. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8067-DAMCHE-014/Candidater.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research
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perforation, and the partial encapsulation or/and amorphisation of the 2D materials. The originality of our project is to design the spatial organisation and density distribution of phonon scattering centers
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a