400 computer-science-intern-"https:"-"https:"-"https:"-"BioData"-"BioData" Postdoctoral positions in United Kingdom
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within a multidisciplinary research team. About the School/Department/Institute/Project The School of Engineering and Materials Science is a large, multidisciplinary School with a strong international
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(Department of Chemical Engineering, Waterloo Institute for Nanotechnology). Program Details: UM6P will be the administrative body for the program, where candidates will apply to the UM6P Postdoctoral Program
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impact? We are currently seeking a/an University Assistant postdoctoral 37 Faculty of Business, Economics and Statistics Startdate: 01.02.2026 | Working hours: 40 | Collective bargaining agreement: §48
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to improve the impact of AI on global societal outcomes through impactful research that is rigorously grounded in the social and computational sciences, decision-maker education campaigns, and training
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. The postholder will be physically based at Trinity College Dublin, embedded in the School of Computer Science and Statistics, Artificial Intelligence Discipline, and the Trinity College Institute of Neuroscience
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team on forefront science, while profiting from the international environment in the Department of Astrophysics . We have privileged access to the Austrian Scientific Computing super-computing facility
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Martin AI Governance Initiative (AIGI Oxford) seeks to improve the impact of AI on global societal outcomes through impactful research that is rigorously grounded in the social and computational sciences
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We are seeking two full-time Postdoctoral Research Assistants in Machine Learning to join the Foerster Lab for AI Research group at the Department of Engineering Science (central Oxford). The post
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and Botswana International University of Science and Technology. A PhD in a Biological Science, Computer Science, Mathematics or Statistics, and relevant experience modelling population dynamics
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. Richard Nickl and work in the project area 'Statistical aspects of non-linear inverse problems', which broadly addresses mathematical and foundational challenges in contemporary data science and the theory