125 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" research jobs at University of Oxford
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travel and Season Ticket travel loans. All applications must include a CV, Supporting Statement/Cover Letter. For further guidance and support, please visit https://www.jobs.ox.ac.uk/how-to-apply. Any
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on the application process at https://www.jobs.ox.ac.uk/application-process The closing date for applications is 12:00 midday on 7 January 2026
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biology, mathematical and computational finance, numerical analysis, machine learning and data science or the Oxford Centre for Industrial and Applied Mathematics (OCIAM). The successful candidates will be
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We are looking for a Research Assistant Reporting to Prof Yee-Whye Teh. The post holder will be a member of Oxford Computational Statistics and Machine Learning (OxCSML) with responsibility
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-to-phenotype models for human health at the Big Data Institute (BDI), University of Oxford. The successful candidate will contribute to a strategic research programme integrating population-scale biomedical data
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fundamental research, we create widely used open-source software including autodE, cgbind/C3, and mlp-train. Our recent advances in Machine Learning Interatomic Potentials (MLIPs) form the foundation of our ERC
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at the intersection of artificial intelligence, multi-omics integration, and cellular systems modelling. Based at the Big Data Institute (BDI) at the University of Oxford, the successful candidate will join the Ideker
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, enthusiastic and willing to learn new skills. You will have highly effective verbal and written communication skills with all level of staff and an ability to operate effectively in a demanding and
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application of AI and machine learning models to interpret complex X-ray datasets, and the integration of experimental and computational insights to generate actionable knowledge that advances sustainable metal
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The postdoctoral researcher will lead the development of computational methods for aligning cortical organisation across species using transcriptomic and anatomical data combined with modern machine