Postdoctoral Research Assistant in Multimodal Analysis of Medical Procedures
Develop machine learning and multimodal video analysis models to understand medical procedures and healthcare skills training.
Best for:Best for computer vision researchers with experience in medical video analysis, multimodal learning, and machine learning model development.
Overview
The University of Oxford is seeking a creative and motivated postdoctoral researcher to join the Turing AI World-Leading Fellowship research programme led by Professor Alison Noble. Based at the Institute of Biomedical Engineering within the Department of Engineering Science, the appointee will focus on the 'AI to understand human skills' research strand. The role involves bridging theory and application by building advanced machine learning models to analyze medical videos, model medical procedures, and evaluate usability through quantitative performance and qualitative human factors assessments. The successful candidate will work within a collaborative, interdisciplinary team alongside clinical and human factors experts over a fixed 18-month term.
What you'll do
- Design and pilot test machine learning-based automated medical video and multimodal analysis models.
- Investigate computational methods to understand medical procedures using video and sparse training data.
- Collaborate with clinical experts and human factors specialists to formulate blue-sky research questions from first principles.
- Evaluate model performance through rigorous quantitative studies and human factors assessments in simulated and real clinical settings.
- Contribute to an interdisciplinary research team aiming to support healthcare professional skills training through AI.
Requirements
Degree required: PhD/DPhil in a relevant field (or near completion)
Language: English
Instruction: English
Publications: Publications in medical image/video analysis, computer-assisted intervention, or video analysis in computer vision required.
- Solid technical experience in medical video or multimodal analysis
- Proven track record in building efficient learning approaches from sparse data
- Demonstrated research background in medical image/video analysis, computer-assisted intervention, or computer vision video analysis
- Open-mindedness to co-develop interdisciplinary research questions with clinical collaborators
- Strong publication record in relevant academic venues
- Must hold a relevant PhD/DPhil or be near completion
Funding & terms
How to apply
Deadline: 2026-11-02
Candidates must submit an online application through the university recruitment portal before the specified deadline. The submission must include a covering letter with a brief statement of research interests, a curriculum vitae, and contact details for two referees.
- CV
- Cover letter
- Research statement
- 2 reference letters
Contact
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.