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), and the PhD student will be involved in several collaborative projects. During the second year of the thesis project, the work will be carried out in close collaboration with our colleagues
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for ambitious PhD research, with rigorous scientific supervision. The PhD student will join the transverse SiC research axis, which is highly dynamic and internationally recognized. He/She will benefit from a
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Description The PhD candidate will contribute to a fundamental research project in cognitive neuroscience aimed at improving our understanding of the neural mechanisms involved in human decision-making during
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are reaching their limits in the face of the increasing complexity of distributed energy systems. The simultaneous presence of multiple energy sources, frequent topology changes, interactions between physical
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Information Additional comments Constraints and risks • Schedule and commitment of the PhD candidate: - 1st year: presence in Paris, training and preparation for fieldwork -2nd year: fieldwork 12 months minimum
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integrated into the LMBA at the Brest campus. They will participate in scientific activities, including lab seminars, team seminars, and PhD student seminars. They will also organize regular meetings with
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD project will
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The successful candidate will join the Climate Physics team at ENS de Lyon (https://climatephysics-ensl.fr/ ), which currently consists of 5 permanent researchers, 7 PhD students and 2 postdoctoral researchers. We
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3 Jul 2026 Job Information Organisation/Company CNRS Department Institut de Biochimie et Génétique Cellulaires Research Field Mathematics History » History of science Researcher Profile First Stage Researcher (R1) Application Deadline 23 Jul 2026 - 23:59 (UTC) Country France Type of...
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French multinational company and a world leader in the production and processing of industrial minerals, serving a wide range of high-performance industrial applications. This PhD project is part of