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: This project is an interdisciplinary effort at the frontier between Biology (Genetics, Genomics), Bioinformatics, Artificial Intelligence (Neural Networks) and Statistics (LMMs). The aim is to join the
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karstic networks and alluvial terraces lying on the top of the foothills. The work will be mainly based on already existing and new TCN dates in order to: (1) gain an overview of the oldest remaining
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physics is especially interesting due to the presence of exotic excitations, potentially non-Abelian. The TensQHE project aims to develop modern numerical tools based on tensor networks, within an open
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of quantum information science, tensor network theory, and generative modeling (transformers, diffusion models, etc.). - Conduct cutting-edge research at the intersection of quantum information, machine
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they interact in a bipartite network and with abiotic environmental changes - mathematical developments - coding - tests with simulations - data analyses - paper writing - presenting results
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work focused on extending methods for detecting the pose of an object (possibly occluded, even if only partially) held by a person to 360-degree robot vision, in line with mesh detection and
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of the world's 34 biodiversity hotspots. The Avoid-Reduce-Compensate sequence that the project owner, SNCF Réseau, must implement, aims to guarantee no net loss of biodiversity induced by the project
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their structure. Small-angle X-ray scattering analysis (SAXS), already used others systems, has proven effective in this regard, providing quantitative information on the key parameters of a structured network in
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waves from shots). The postdoctoral researcher will use data acquired in Ecuador on a 3D network of ocean bottom seismometers and land stations. As part of Mission 1: 1. Implementation/adaptation
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the synthesis of the nanowires and their assembly into networks (by soft chemistry), while the synthesis of the matrix (CVD deposition) will mainly be carried out by a PhD student already recruited