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computational inference (SuperStoc group, ERC), with strong ties to experimental collaborations within the Turing Centre for Living Systems (Centuri, Aix-Marseille Université). The thesis will combine theory
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collaborations with biophysics laboratories. The project lies at the intersection of artificial intelligence, machine learning, computational physics, and molecular biology, and aims to contribute new
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the context of a PEPR project, in collaboration with eight CNRS and CEA laboratories working on the future of electrical grids. More specifically, it is linked to WP5, dedicated to cybersecurity and network
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collaborative project. Under the joint supervision of Dr Nikolski and Dr Engelhardt, the candidate will become an integral part of both teams. The PhD candidate will develop and apply AI/bioinformatics
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archaeological and historical contexts is also required. Additionally, the ability to perform *ad hoc* data processing (multivariate statistics, machine learning, etc.) is desirable. Proficiency in programming
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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