376 machine-learning "https:" "https:" "https:" "https:" "The Open University" positions at University of Oxford
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, learning under uncertainty) that is of an international standard, and that is carried out expertly, rigorously and in accordance with ethical guidelines. You will also participate actively in the lab
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guidance at https://www.jobs.ox.ac.uk/cv-and-supporting-statement. The closing date for applications is 12.00 noon on Monday 9th February 2026. Only applications submitted by this time will be considered.
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. Please see the University pages on the application process at https://www.jobs.ox.ac.uk/application-process The closing date for applications is 3 February 2026 Interviews will take place during week
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support for conferences, training, or public involvement activities, subject to approval. Details of course fees are available here: https://www.ox.ac.uk/admissions/graduate/courses/dphil-psychiatry
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Earth Centre for Doctoral Training (CDT) in AI for the Environment. (https://intelligent-earth.ox.ac.uk/home) Applications for this vacancy are to be made online. You will be required to upload a CV and
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Research Council rate (currently set at £20,780 p.a.) for 3.5 years. Please note the eligibility criteria set out by the UKRI at: https://www.ukri.org/what-we-do/developing-people-and-skills/esrc/funding
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colleges, and discounts at University museums. See https://hr.admin.ox.ac.uk/staff-benefits Application Process Applications for this vacancy are to be made online. You will be required to upload a
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opportunity to pursue an independent programme of research in this critical area and to join Oxford University’s Tuberculosis Grand Challenge (https://www.ineosoxford.ox.ac.uk/ioi-grand-challenge-tuberculosis
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the laboratory and improve them on the basis of their performance to recognise drug induced cell morphologies About You You will have an MSc or equivalent qualification in mathematics, machine learning, LLMs, and
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will have a background in contemplative neuroscience and experience with machine learning approaches such as support vector machines, gradient boosted trees, or convolutional neural networks. A Master’s