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collisions at the LHC (ATLAS) and prospective future colliders (CEPC/SppC); and related theoretical efforts. The division has an active visitor program and co-organizes several conferences and workshops
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, Shanghai 200092, China [map ] Subject Areas: All fields of mathematics, including but not limited to: • Pure Mathematics • Applied Mathematics • Computational Mathematics • Mathematical Physics • Statistics
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, treatment planning, and patient care. The research will involve data collection and preprocessing, model architecture design, pre-training and fine-tuning, evaluation and benchmarking, and model optimization
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Institute of Mathematical Sciences and Applications (BIMSA) invites applications for several postdoctoral positions in all fields of mathematics, theoretical physics, computer science, and their applications
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comprehensive "undergraduate - master - doctor" talent training system. Currently, it hosts a postdoctoral research station in mathematics, a first - level doctoral program in mathematics, and a first - level
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for various omics data, including microbiome, genetics, genomics, and metabolomics data. The position is for a two-year appointment. Applicants must hold a PhD in Statistics, Biostatistics, Bioinformatics
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internationally competitive annual salary (RMB 300K+; negotiable) and benefits including excellent medical insurance, rent-subsidized on-campus housing, children‘s education and retirement plan. You have the
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or continuously monitord systems are especially encouraged to apply. However, other research profiles, within the realm of theoretical physics, especially will also be seriously considered. Requirements: A PhD
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written and verbal communication skills in English. 4. Preference will be given to candidates experienced in using Sage, PARI/GP or Magma to do number theoretic computations (L-functions, modular forms, etc
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conjecture, -- Langlands program and related problems, -- algebraic geometry and complex geometry, -- partial differential equations and in particular Navier-Stokes equations, -- stochastic analysis