71 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Postdoctoral research jobs at University of Oxford in United Kingdom
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to the 30th September 2026. We are looking for outstanding machine learning researcher to join the Torr Vision Group and work on AI Scientists: systems that use foundation models, AI agents, and robotics
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* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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the sequence of the human genome and the development of common diseases. You will work on a collaborative project that aims to develop Machine Learning and laboratory-based approaches, for decoding how the human
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the next generation of PV technologies for beyond 2030. The new postdoctoral research position will use materials modelling techniques (DFT, molecular dynamics, machine learning potentials) to investigate
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(PI), Saiful Islam, Peter Bruce), with UCL Chemical Engineering (Dr Rhod Jervis) and 4 industrial partners that brings together expertise in battery materials synthesis and device fabrication, advanced
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research project lead by Oxford Materials (Professors Robert House (PI), Saiful Islam, Peter Bruce), with UCL Chemical Engineering (Dr Rhod Jervis) and 4 industrial partners that brings together expertise in
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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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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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part of your online application. Please see the University pages on the application process at https://www.jobs.ox.ac.uk/application-process The closing date for applications is 3rd March 2026. It is
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application. In your supporting statement, please explain how you meet each of the selection criteria found in the job description, and why you would like to do this role. See guidance at https