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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database
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Environment (UMR5300; https://crbe.cnrs.fr/en/ ) is internationally recognized for its research on the interaction between the environment and biodiversity using genetics. Numerous projects are being developed
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Information Eligibility criteria Applicants should hold a PhD in theoretical chemistry, physics, materials science, or a related field; -demonstrate strong expertise in machine learning (regression, neural
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manual gestures). The SyncoGest project (2025–2030) is an interdisciplinary project conducted jointly by computer scientists (Loria – University of Lorraine / Inria / CNRS), linguists (Praxiling – Paul
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or by car (parking available). Public transportation costs are partially covered. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7104-MARMEN-001/Default.aspx Requirements Research
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of results at conferences - interaction with team members and international collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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experience in scientific programming is a plus. • Experience in constructing Machine Learning potentials would be appreciated. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5254
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has opened a new era in the exploration of the fundamental laws of Nature, and it will be the world's energy frontier machine for the foreseeable future. After the breakthrough discovery of the Higgs
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the supervision of students (interns and/or PhD candidates) -preparation of scientific publications and progress reports -presentation of results at national and international conferences This work will be carried