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layered semiconductor characterized by an anisotropic crystalstructure and quasi-one-dimensional ribbon-like morphology. Its electronic structure is predicted to host relatively flat bands associated with
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on the linguistic analyses provided; o Evaluating the results of the prediction and classification models developed by Loria. Praxiling is a Joint Research Unit (UMR 5267) under the joint supervision of the CNRS and
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Shell Model with Continuum and its extensions to construct high-fidelity microscopic optical potentials, designed for use in few-body reaction formalisms, in particular Faddeev-type calculations targeting
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/develop predictive models that can inform future land management and conservation strategies. Responsibilities • Data mining: Compile, review and complete pollen data and age-depth models from existing
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methods to understand and predict the adsorption, self-assembly, and protective behavior of N-heterocyclic carbenes (NHCs) on metallic and oxidized surfaces. NHCs are promising corrosion-inhibiting
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methods to integrate transcriptional and cellular dynamics. Analyze large-scale transcriptomic and spatial dynamics datasets. Work in close collaboration with the team's biologists to test predictions from
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that incorporates a broad range of neutrino and dark-matter models, assessing their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps
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predictions of the models. Placement: La Rochelle Université, laboratory LaSIE, UMR 7356 CNRS Recruitment: fixed-term contract 12 months Working hours: full time Contract starting: Spring 2026 Salary: According