354 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at University of Oxford
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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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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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to undertake analyses of neuroimaging measures, apply machine learning approaches to clinical and neuroimaging data, the development of clinical services, the conducting of meta-analyses, and the analysis of pre
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of competitive benefits available to all staff for both work and personal life - https://hr.admin.ox.ac.uk/staff-benefits For informal enquiries about the post, please contact Ellie Tzima – ellie.tzima
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contribute to monitoring performance through reporting and analysis. You will also represent the Museum professionally in trade contexts, including promotional activity and trade events, and share learning and
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be released for a secondment before you submit an application https://hr.admin.ox.ac.uk/secondments Only applications received online by 12.00 midday (BST) on Tuesday 7 April 2026 can be considered
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to upload a covering letter/supporting statement, CV and the details of two referees as part of your online application. Please see the University pages on the application process at https://www.jobs.ox.ac.uk
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at the CNCB, which shares responsibility for the running and maintenance of the facility. More information about the Goodwin lab can be found at: https://www.cncb.ox.ac.uk/the-science/research-groups/goodwin
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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