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organ transplantation. HLA-Epicheck is a predictive model of the antigenicity of polymorphic amino acids on the surface of HLA antigens, relying on dynamic structural data. Four tasks are identified. Task
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numerical validation of error bounds for model-order reduction based on optimal transport, in the context of electronic structure calculations. The postdoctoral researcher will be assigned to the Besançon
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. The objective is to extract structural and metabolic biomarkers enabling precise spatio-temporal modeling of tumor evolution, for diagnosis, prognosis and personalized therapeutic follow-up. Develop deep learning
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) or electrodes in lithium-ion batteries samples as the project advances. The results of the ptychography will be correlated with both chemical as well as structural three dimensional analysis of the same sample
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called MCTPs (Multiple C2 domains and Transmembrane region Proteins) forming a tightly constricted tubular ER structure surrounded by a PM tube. PD operates as critical routes for communication and
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19 Sep 2025 Job Information Organisation/Company CNRS Department Sciences et Ingénierie, Matériaux, Procédés Research Field Chemistry Physics Technology Researcher Profile Recognised Researcher (R2) Country France Application Deadline 9 Oct 2025 - 23:59 (UTC) Type of Contract Temporary Job...
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contribute to various aspects of the project, such as: - developing new theoretical approaches to model electrode/electrolyte interfaces - performing molecular simulations, such as molecular dynamics
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recognized for the excellence of its research. The DYNAMO team is internationally recognized in particular for its work on the development of IRMPD, a method it has pushed to applications. With advances in
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far from straightforward. In particular, estimates of transfer rates based on documented cases are both biased and approximate. This project aims to develop explicit phylogenetic models of TE evolution
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approach that includes cross-section calculations, the development of Monte Carlo codes, and the advancement of the NanOx model for biological dose prediction. As part of a collaboration with the University