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Field
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Additional Information Eligibility criteria Training and experience: A PhD in Materials Science, Computational Chemistry, Physics, or a related field, with a strong background in DFT modeling and experience in
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Computational Cost by Machine Learning and DFT-Based Data, Journal of Chemical Theory and Computation, 2024, 20 (16), 7287–7299. Funding category: Contrat doctoral PHD Country: France Where to apply Website https
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) Positions Postdoc Positions Application Deadline 17 May 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme
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) Positions PhD Positions Application Deadline 15 May 2026 - 12:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The postdoctoral researcher will join the LIMA
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interdisciplinary research at the interface of biology, physics, and computation ● Experience in image analysis and/or machine learning is highly desirable ● Programming skills (Python or equivalent) are a plus
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interface scripts, run jobs on High Performance Computing (HPC) clusters and develop new functionalities in Biom3d like preprocessing OME-Zarr images. Eligibility criteria Significant experience in Python
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benefit from a structured training programme, including transferable skills and scientific courses. The PhD will take place in a multidisciplinary research environment with access to state-of-the-art
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a EU programme Reference Number PEPR-DIADEM Is the Job related to staff position within a Research Infrastructure? No Offer Description The present PhD proposal is part of the project AMMETIS[1] (AI
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sciences First enrollment for a PhD in 2026–2027, in sociology or anthropology Where to apply Website https://recrutement.ehess.fr/828_offre-emploi-doctorante-contractuelle-pour-le-… Requirements Research