Location: | Oxford |
---|---|
Salary: | £38,674 to £46,913 per annum. Grade 7 |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 21st May 2025 |
---|---|
Closes: | 17th June 2025 |
Job Ref: | 179871 |
Location: Department of Engineering Science, in collaboration with Experimental Psychology and in association with St Catherine’s College
We are seeking a creative and highly motivated postdoctoral researcher to join the Turing AI World-Leading Fellowship research programme led by Professor Alison Noble. This exciting and ambitious research aims to develop new AI for shared human-AI decision-making in healthcare imaging. This post is focused on AI-assisted ultrasound guidance building on the group’s prior work on video and multi-modality ultrasound analysis. The appointee will be part of the Noble research group at the Institute of Biomedical Engineering, based at the Old Road Campus in Headington. The post is funded by UKRI and is fixed-term for two years in the first instance.
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 testing of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated and real clinical scenarios. Evaluation may involve quantitative studies (model performance) and quality studies (human factors assessment).
You should hold a relevant PhD/DPhil (or be near completion) in computer vision or robotics or biomedical image analysis. Knowledge of ultrasound imaging is not a requirement. You should have a strong publication record at the principal conferences and/or journal publications dependent on your background discipline(s) and should hold sufficient theoretical knowledge of deep learning-based methodologies as well as working with real-world data.
Informal enquiries may be addressed to Prof Alison Noble (email: alison.noble@eng.ox.ac.uk).
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 19 June 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.
Type / Role:
Subject Area(s):
Location(s):