Postdoctoral Research Assistant in Explainable Medical Video Analysis

We are seeking a creative and highly motivated postdoctoral researcher to join the COCHE project led by Professor Alison Noble. This exciting and ambitious research aims to develop new AI for analysis of fetal echocardiography video sweeps in support of simplifying earlier detection of congenital heart conditions in  pregnancy. The post involves developing new AI-based ultrasound video analysis methods which will be validated in collaboration with clinical partners as part of the research. 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 InnoHK and is fixed term until 30 November 2025.

You will be responsible for the design and testing of original machine-learning based methods for detecting heart anatomy and disease from short ultrasound video sweeps as part of a collective effort to develop a suite of automated analysis tools to support earlier detection of congenital heart conditions. There are interesting technical challenges in doing this which require thinking about domain adaptation in video analysis, and clinical interpretability of outputs to ensure that the AI model is trusted. You may also support clinically led research exploring clinical adoption of this new technology, and on-going data collection and (manual and automatic) annotation efforts from the multiple sites we partner with.

You should hold a relevant PhD/DPhil or be near completion, in Computer Vision or Biomedical Image Analysis. You should have a strong publication record at the principal international computer vision or medical image conference/journal publications dependent on your background and should hold sufficient theoretical and practical knowledge of deep learning-based methodologies and statistical learning.

Informal enquiries may be addressed to Prof Alison Noble (email: alison.noble@eng.ox.ac.uk).

For more information about working at the Department, clcik the 'Apply' button above. 

Only online applications received before midday on 25 October 2023 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of how research (describing how past experience and future plans fit with the advertised position), CV including highlighting your top three papers, 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.

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