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. Requirements: We are looking for a highly motivated candidate with a PhD in theoretical/computational physics or applied mathematics. A strong background in quantum mechanics and numerical simulations is
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 11 days ago
and mentor interns and PhD students within the QAT team. Participate in the scientific integration and dissemination activities Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2025
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) on the VLT UT4. Where to apply E-mail recrutement@oca.eu Requirements Research FieldAstronomy » AstrophysicsEducation LevelPhD or equivalent Skills/Qualifications The fellow will be integrated in the LAGRANGE
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. The position will involve the use of molecular tools to generate transgenic parasites, advanced imaging techniques and the implementation of new chemoproteomic protocols. Parasite culture, biochemistry and
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), - land use planning, social vulnerabilities, and economic issues (inequalities, accessibility, human development). This research and its contribution to public policy are based on methods and techniques
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. Placed under the hierarchical responsibility of the lab's Director, the recruited person will work in close collaboration with the leader and coordinator of the ANR DYRE-COMB project. Where to apply
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sedimentology of microbial carbonates, applied to the characterization of paleoenvironments, or more broadly to surface processes. The candidate should have fieldwork experience and be familiar with optical
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potential lends itself to this. Required profile: · With a PhD in physics or mechanical engineering, the successful candidate will have acquired solid skills in the mathematical and numerical methods
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experience would be an asset. EXPECTED SKILLS : Design and lead sample collection Operate effectively in a clean lab environment Apply element separation protocols Process data using appropriate mathematical
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learning or applied mathematics. Required skills and qualities: - Fluency with Python programming for data analysis or machine learning, - Knowledge of statistical or probabilistic modelling techniques