Research Associate Deep learning and Fetal Neurosonography

Computer Science - Wolfson Building, Parks Road, Oxford The post-holder will contribute to cutting-edge research at the intersection of deep learning, computer vision, and biomedical imaging. This includes exploring efficient network designs, contributing to the development of novel learning-based representations for geometric reconstruction, and integrating insights from neural rendering into medical imaging workflows. A major focus will be on accelerating inference and training using GPU-optimised components, including custom CUDA kernels. This role offers a unique opportunity to push the boundaries of neural scene representations in a medical imaging context. The successful candidate will work alongside a multidisciplinary team of deep learning researchers, computer vision experts, and clinicians, designing scalable and responsive tools that directly support prenatal brain imaging at the bedside. The candidate will also benefit from co-supervision by Dr Joao Henriques from the Visual Geometry Group (VGG).
The successful applicant will report to the project PI, Professor Ana Namburete. The position is available from September. Flexible working
This is a full-time role (37.5 hours per week) that requires on-site working. Some flexibility may be possible, depending on work needs, such as attending in-person meetings or travelling for conferences. What We Offer
As an employer, we genuinely care about our employees’ wellbeing and this is reflected in the range of benefits that we offer including: • An excellent contributory pension scheme • 38 days annual leave (pro-rata for part-time roles) • A comprehensive range of childcare services • Family leave schemes • Cycle loan scheme • Discounted bus travel and Season Ticket travel loans • Membership to a variety of social and sports clubs Diversity
Committed to equality and valuing diversity. Application Process