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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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analysis, scientific computing, algebraic topology and non-linear analysis. The activities may include: The development of new polytopal numerical methods The conception of discrete complexes (de Rham and
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. Baschnagel. Correlations of tensor field components in isotropic systems with an appli- cation to stress correlations in elastic bodies. Phys. Rev. E, 108:015002, 2023. [7] J. P. Wittmer, A. N. Semenov, and J
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metric tensor associated with the growth field: The further Ricci is away from zero, the more incompatibility. The goal of this project is to better understand the mechanical origin of residual stress in
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) understanding of the mathematical foundations and principles of Machine Learning, Linear Algebra (vectorial and matricial operations, optimization), with a particular focus on Neural Networks, 3) problem solving
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candidate will work with the PI of the project (André Belotto da Silva) and with the Singularity Theory group at the IMJ-PRG. Research activities in the fields of Singularity Theory, Algebraic Geometry, and
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) forms, Iwasawa theory, algebraic cycles, Shimura varieties, p-adic Hodge theory.. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UAR822-SOPRIB-008/Default.aspx Work Location(s