261 structures "https:" "https:" "https:" "https:" "https:" "https:" "Birmingham Newman University" Postdoctoral positions at CNRS
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calculus, type systems, and models for probabilistic programming languages. Permanent members : A. Saurin, T. Ehrhard, C. Faggian, P.-A. Melliès, D. Kesner, G. Bernardi. Where to apply Website https
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involved and stakeholders interested in the project. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8538-PIEBAR-007/Candidater.aspx Requirements Research FieldEnvironmental scienceEducation
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diffractometer, a GC for common gas analysis, a GC/MS, and an HPLC/MS. DFT calculations will be performed using annual allocations on national high-performance computing centers. More details here: https
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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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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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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 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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. Postdoctoral researchers will have access to state-of-the-art imaging and cellular biology platforms, as well as a dynamic international research environment. Where to apply Website https://emploi.cnrs.fr
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model's development. The position is based at LOCEAN on the Pierre and Marie Curie campus of Sorbonne University. The LOCEAN laboratory (https://locean-ipsl.upmc.fr ) is one of nine laboratories in
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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