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• Switzerland: P. Herrera • Netherlands: A. Zaldumbide • Portugal: Q. Zhang • UK: B. Hastoy Collaborations in France: • P.-D. Denechaud (Toulouse) – adipose tissue and transgenic models • S. Renaud, J. Cieslak, M
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. This PhD project in Natural Language Processing aims to design generative models capable of automatically simplifying texts into Easy-to-Read and Understand language while preserving their discourse
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to the development of energy models; • to access complementary experimental platforms; • to strengthen Franco-Canadian scientific collaborations. The project also benefits from industrial support through
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resistance of ceramic shell moulds used in investment casting. Advanced in situ experiments combined with multi-scale Finite Element Method (FEM) modelling will be employed to identify the key stress and
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deceased from H5N1 and 10 exposed but healthy) will be compared to the historical cohort. This step will aim to identify new signatures of genetic selection and model population resilience through population
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, neurodegeneration, advanced microscopy, stem cell biology, and cell biology. The project will leverage state-of-the-art imaging facilities and established human iPSC-derived models of Alzheimer's disease. The work is
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Website https://emploi.cnrs.fr/Offres/Doctorant/UMR8180-CLEGHI-002/Default.aspx Requirements Research FieldChemistryEducation LevelMaster Degree or equivalent Research FieldEnvironmental scienceEducation
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) programme. The discovery of the Higgs boson by the ATLAS and CMS experiments in 2012 completed the Standard Model (SM) of particle physics by confirming the mechanism of electroweak symmetry breaking (EWSB
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methodological developments along the chosen direction (inference, active-matter theory, or machine learning). ◦ Algorithmic implementation and validation of the developed tools. 5. Validation on model systems
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Belfort-Sévenans. The primary objective of this doctoral thesis is to reconsider current models related to economic structures and the connectivity of human communities during the early Middle Ages (6th