105 structures-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" research jobs at CNRS in France
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resolution of crystal structures. - Experience with glove box under argon atmosphere and eventually with air sensitive materials. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5253
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be authorized by the competent authority of the Ministry of Higher Education, Research and Innovation (MESR). Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8180-DAVKRE-007
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and develop a nonlinear absorber to control very low-frequency vibrations in an underwater structure. The project will have a scientific focus on studies in vibroacoustics and nonlinear dynamics from
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neuroimaging data constrained by patient's structural connectivity and tractography • Using the results of the TVB model fits to stratify patients and predict disease progression • Organizing and unifying
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charge/discharge cycles. The aim is to provide a unique tool to better understand the structure and evolution of interfaces/interphases in batteries, and thus, guide the design of more efficient and
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technology. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5237-HIEPHA-008/Candidater.aspx Requirements Research FieldChemistryEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD
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the development of flexible nanozeolites. This position offers a unique opportunity to explore the structural dynamics of nanozeolites under varying conditions and contribute to advancing green
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of the ANR Lamorsim project (https://anr.fr/Project-ANR-23-CE08-0029 ). The main objective of this project is to develop methodologies for achieving controlled laser-induced amorphization of silicon. In this
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of contributions to the international ePIC (electron Proton-Ion Collider experiment) collaboration associated with the construction of the future Electron-Ion Collider (EIC, Brookhaven National Laboratory -BNL, New
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the flexibility and power of NNs with the ability of LMMs to robustly learn from structured and noisy (non i.i.d.) data, applying them on the prediction of both plants and human phenotypes. These models will