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. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UPR2940-LEIMOG-012/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD
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imaging setups, XRF scanners, micro-XRF, and synchrotron XANES), as well as guidance at the intersection of paleontology, biology, and physical chemistry. Where to apply Website https://emploi.cnrs.fr
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within the research group; - develop and troubleshoot experimental strategies; - contribute proactively to the formulation of biological questions and the interpretation of results; - present research
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of the technology, one of whose key areas (the subject of this postdoctoral position) is to design and develop innovative materials combining catalytic efficiency, electrical conductivity, and mechanical strength, in
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
of Copenhagen (UCPH), alongside Universidad Rey Juan Carlos (URJC, ES), University of Twente (UTWENTE, NL), Copenhagen Academy for Medical Education and Simulation (CAMES, DK), InSimo (FR), AMBU A/S (DK) and
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oxides, we will first develop and benchmark machine-learning interaction potentials of increasing complexity. Subsequently, we will deploy a combination of brute-force and rare-event sampling to isolate
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responsibilities The successful candidate will: Conduct independent and collaborative research within the project. Design and perform experimental research programmes. Synthesize monomers and thermosets Develop
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platforms and 1,600 partner companies. For more information: https://www.imt-mines-ales.fr You will be affiliated with the Center for Research and Teaching in Environment and Risks (CREER) at IMT Mines Alès
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, technicians, and administrative personnel. Please note that this position falls within a sector subject to protection of scientific and technical potential. Where to apply Website https://emploi.cnrs.fr/Offres
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collaborations to implement cosmological analyses derived from the observation of Type Ia Supernovae. This work, carried out within the framework of the ANR SCINF project, aims to develop inference methods based