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RESEARCHER (M/F) with the ANR MIJMA (International Migration of Young Africans and Minors to Europe.
). The Laboratory of Economics and Sociology of Work (LEST, http://www.lest.cnrs.fr ) is a joint unit of the CNRS and Aix-Marseille University, specialising in the analysis of work and its various spheres as a
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Université Paris-Saclay. Job profile: • Researcher in theoretical/computational condensed matter physics. • Strong proficiency in programming and genuine interest for numerical methods • Solid background in
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” team. Website: https://cermav.cnrs.fr/en/equipe/physico-chemistry-and-self-assembly-of… Team Leader: R. Borsali The successful candidate will be responsible for synthesizing glycopolymers based
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Additional Information Website for additional job details https://www.ietr.fr/en/techno-economic-studies-grid-capacity-allocations-future… Work Location(s) Number of offers available1Company
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City Montpellier Website http://www.umontpellier.fr/ Street 163 rue Auguste Broussonnet Postal Code 34000 E-Mail frederic.cuisinier@umontpellier.fr STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn
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preparation platform, SSMIM - Resources provided (equipment, IT, etc.): Computer workstation, binocular magnifying glass, analytical equipment (IRMS mass spectrometer) Where to apply Website https
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. The RITMEA project is co-funded by the European Union, the French State, and the Region Hauts-de-France. Where to apply Website https://utc.recruitee.com/o/chercheur-contractuel-fh-navigation-et-localisation
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the Luxembourg Financial Center, the European Stability Mechanism, the Central Bank of Luxembourg and other economic and financial institutions located in Luxembourg. Your profile We are looking for candidates
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in the Khaybar oasis during the Islamic period. The researcher will be hosted within the UMR 7298 team in Aix-en-Provence. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7298-DIAALB
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degree in computer science or a closely related field Solid background in AI, with particular interest or experience in foundation models e.g., representation learning, large‑scale pretraining, and graph