342 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at University of Oxford
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experience working with frontend/backend web development, machine learning, or high performance computing would be desirable, as would any experience designing or delivering training courses. This post is
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teach, supervise, and examine undergraduate and postgraduate students. Applications are particularly welcome from women and black and minority ethnic candidates, who are under-represented in academic
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professional services. For more information please visit: https://finance.admin.ox.ac.uk/ What We Offer Working at the University of Oxford offers several exclusive benefits, such as: • 38 days of annual leave
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have the Right to Work within the UK as this position may not amount to enough points under the points-based immigration system in the UK. For more information please visit: https://www.jobs.ox.ac.uk/pre
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to https://www.jobs.ox.ac.uk/cv-and-supporting-statement for information and advice on writing an effective Supporting Statement. This role is full time (part time considered) and is fixed term for 2
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area. You will possess sufficient specialist knowledge in the discipline of neurodiversity to work within established research programmes. An experience in engaging in Human-Computer Interaction (HCI) based
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, engaging learning environment for postgraduate students. Alongside teaching, you will develop an independent research programme aligned with one or more of the ECI’s research themes, including Climate
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relevant learning to professionals worldwide. Alongside this, you will pursue original research aligned with the TSU’s research programme, generating high-quality publications, contributing to funding
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research and education by collaborating on sound financial strategy to provide long-term resources, underpinned by excellent operational and professional services. For more information please visit: https
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3.5-year D.Phil. studentship Supervisors: Prof Noa Zilberman The training of new AI models, as well as their deployment for inference, is transforming the design of computer networks. In