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researchers in pursuit of advancing knowledge and making significant contributions to their respective fields. ESSENTIAL QUALIFICATIONS/EXPERIENCES PhD Graduation; Strong background in deep learning, machine
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. - Research Areas: Positions are focused around Deep Learning and Inverse Problem Regularization. Successful candidates will engage in diverse projects ranging from provincial to national levels, in
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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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of expertise of an applicant are pure, applied or computational mathematics. The successful candidate will have no obligation to teach, but will be required to apply for an external funding from National Natural
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particle physics or related areas prior to the time of employment. Preferences will be given to those with experiences in collider phenomenology, machine learning, effective field theories, positivity bounds
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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
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of China, Sub-projects of the National Science and Technology Support Program, the National Spark Program, and Key R&D programs in Hainan, Guangxi, and Jiangsu provinces, as well as industry-funded
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Research associates (at the level of non-tenure assistant professor, through CAS Special Research Assistants’ program). The applicants should send/arrange the following documents: 1. curriculum vitae
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Location: Shanghai, Shanghai 201210, China [map ] Subject Area: theoretical and computational studies of condensed matter physics / theoretical and computational studies of condensed matter physics Appl
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Postdoctoral Program," offering enhanced compensation and the opportunity to directly transition into an Associate Professor role upon completion. - Additional Benefits: Includes social security, housing funds