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), within the ATLAS group. The PhD student will join a large-scale international collaboration and participate in the activities of the ATLAS experiment at CERN. The work will focus on the analysis of data
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, combined with automated sampling and complementary physicochemical analyses. This collaboration will provide advanced training in the correlation between polymerisation, self-assembly mechanisms
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research axis, which centers on representations and symbolic behaviors in the Paleolithic. You will also collaborate closely with Patrick Tardivel, a mathematician at the Institut de Mathématiques de
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), within the ATLAS group, in close collaboration with the French-Japanese ILANCE laboratory and the University of Tokyo. The successful candidate will become part of a large international collaboration and
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intelligence. It promotes strong Franco-Canadian collaborations and offers an ideal framework for hardware–algorithm co-design projects. The scientific organization of the PhD project will rely on close
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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in
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(focusing on polar and alpine environments) and geophysical fluid dynamics. We collaborate with several colleagues from the Physics Laboratory, who are experts in hydrodynamics/climate research (about 15 PIs
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properties of this protein, as well as its interactions with other cellular components. The obtained results will be compared with available experimental data, in collaboration with our partners. We
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. This activity is inherently multidisciplinary with strong collaborations with other scientific fields, as applied mathematics or statistical physics. Fluid mechanics is ubiquitous in geophysical and industrial
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project, which is itself a component of the PostGenAI@Paris project (AI cluster) led by Sorbonne Université. It will benefit from the momentum of this project and the ongoing collaborations with academic