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Postdoctoral Research Assistant in Federated Learning for Healthcare Imaging Research Collaboration
2 months ago
Location: Department of Engineering Science, Institute of Biomedical Engineering, Old Road Campus Research Building, Headington, Oxford, OX3 7DQ
We are seeking a creative and highly motivated Postdoctoral Researcher to join a research programme led by Professor Alison Noble on federated learning for healthcare imaging collaboration. This is associated with her Turing AI World-Leading Researcher Fellowship and a grant that has collected a large multi-site fetal echocardiography dataset of normal and congenital heart disease cases. You will be part of the Noble research group at the Institute of Biomedical Engineering, based at the Old Road Campus Research Building in Headington. The full-time post is funded by UKRI and InnoHK and is fixed-term for 12 months.
You will be responsible for the design and testing of federated learning algorithms for video and multi-modal imaging data acquired at different clinical sites. Prior experience of multi-modal federated learning is a requirement for this post. The research will use both existing clinical datasets and may also involve collaborating with overseas partners to derive and evaluate models and overseas travel.
You should hold a relevant PhD/DPhil (or near completion) in Federated Learning for Healthcare Imaging. You should have a strong publication record at the principal international computer vision and machine learning conferences, or medical image conference/journal publications and should hold sufficient theoretical and practical knowledge of relevant methodologies.
Informal enquiries may be addressed to Prof Alison Noble (email: ).
For more information about working at the Department, see
Only online applications received before midday on 17 September 2024 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.
£36,024 to £44,263 per annum. Grade 7
