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, Bioinformatics, Computational Biology, Computer Science, or a related quantitative discipline. Strong statistical, computational, and communication skills are highly desired. A keen interest in gaining knowledge
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Starting Date 1 Aug 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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Areas: All fields of mathematics, theoretical physics, computer science, and their applications Appl Deadline: (posted 2023/01/03, listed until 2025/10/28) Position Description: Apply Position Description
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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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countries, including EPSRC Programme grant "Symmetries and Correspondence". The principal investigator is Professor Ivan Fesenko. Professor Ivan Fesenko's Higher Number Theory page: https://ivanfesenko.org
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. Preferences will be given to those with experiences in collider phenomenology, machine learning, effective field theories, positivity bounds, scattering amplitudes and their applications to classical
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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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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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offers bachelor's, master's, and doctoral degrees. Research interests of faculty members include core areas of pure mathematics, applied mathematics, information and computational science, and statistics
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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