145 structures-"https:" "https:" "https:" "https:" Postdoctoral research jobs in France
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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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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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within the SAMS Research Group (http://sams.ics-cnrs.unistra.fr/en/ ). PROJECT DESCRIPTION: The post-doctoral researcher will show that by integrating molecular motors into supramolecular self-assemblies
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Communauté d’universités et établissements de Toulouse | Toulouse, Midi Pyrenees | France | 7 days ago
Fellows conduct an independent research project hosted by an eligible Toulouse unit, with structured supervision, a Career Development Plan and advanced training (scientific & transferable skills). Key
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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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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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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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properties. Confocal microscopy / microfluidics / microrheology, to link the structural remodeling of the gel to the reaction kinetics occurring within the material. The identified gelation and structuring
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 2 months ago
-acid complexes. You will join the Delta team at Inria (Université de Lorraine), working closely with Dr. Yasaman Karami, expert in conformational dynamics, allostery, and deep learning for structural
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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