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Postdoctoral Research Assistant in Medical AI

University of Oxford
£38,674 - £46,913 a year
Oxford, England
Full time
3 weeks ago
We are seeking five full-time Postdoctoral Research Assistants to join the Computational Health Informatics Lab at the Department of Engineering Science, based at the Institute of Biomedical Engineering in Headington. The posts are fixed-term for 12 months in the first instance, funded by the NIHR, EPSRC, and the Gates Foundation.
The postholders will work on projects with international collaborators and colleagues from within the University to achieve a range of real-world outcomes. Typical outputs include top-tier scientific publications, patents, and seeing collaborators translate our work into real-world settings.
You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications.
You must hold a PhD (or be near completion) in a field such as AI, computer science, signal processing, biomedical engineering, have a strong record of publication in engineering or computer science literature, and have an interest in the use of AI in healthcare. Proven competence in programming methods in Python and similar environments is also essential.
Informal enquiries may be addressed to Professor David Clifton (email: [email protected]).
For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/.
Only online applications received before midday on the 18 August 2025 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.
The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.
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