We are seeking a creative and highly motivated postdoctoral researcher to join the CAIFE study, a joint project led by Professor Alison Noble (Institute of Biomedical Engineering) and Professor Aris Papageorghiou (Department of Women's and Reproductive Health). This exciting and ambitious research aims to develop new AI-assistive technology for detecting congenital heart conditions (CHDs) from fetal heart ultrasound scans. The Oxford team, in partnership with 5 hospitals sites, has curated a large fetal echocardiography dataset called CAIFE consisting of both healthy and abnormal fetal heart scans. You will be responsible for the design and testing of original machine-learning based methods for fetal heart biomarker discovery from the CAIFE image and video dataset. The full-time post is funded by InnoHK and is fixed term for 24 months.
You will be working in a small highly motivated inter-disciplinary team working towards a shared goal. You will be responsible for the design and pilot testing of original image and video-based CHD biomarkers. You will work closely with clinical domain experts to define and evaluate AI biomarker models. You should hold a relevant technical PhD/DPhil (or near completion) in medical video analysis or computer vision with a video focus and ideally have prior experience of working with echocardiography or fetal echocardiography or related experience on real-world video analysis.
What we offer:
Applications for this vacancy are to be made online via our e-recruitment system and should include the covering letter/supporting statement (describing how you meet the criteria) and including a brief statement of research interests (describing how past experience and future plans fit with the advertised position) a CV, and names of two academic references. The position is a full-time, fixed-term post available for 24 months. The closing date for applications is 12.00 noon on Friday 09 October 2026. Informal enquiries may be addressed to Prof Alison Noble alison.noble@eng.ox.ac.uk.
Tagged as: Life Sciences
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