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Research Associate in Machine Learning for Population Imaging
4 months ago
Location: South Kensington - Hybrid
Job Summary
We are looking for an enthusiastic Research Associate in Machine Learning for Population Imaging, funded by a British Heart Foundation (BHF) New Horizons project. The project is at the intersection of machine learning, population imaging and 3D shape analysis. It aims to develop novel computational and machine learning methods that can reconstruct dynamic 3D-temporal shapes of the four cardiac chambers from multi-view imaging data. The developed methods will be applied to population-level imaging datasets, such as the UK Biobank, to create a large-scale cardiac shape database. Based on the curated database, novel shape analysis and geometric deep learning methods will be developed to understand the variations of cardiac shape and motion on large populations.
The Research Associate will undertake research in medical image analysis, machine learning, and 3D shape analysis, in close collaboration with existing group members and clinical partners. The research outcomes are expected to be published in high-quality refereed international journals and conferences. The successful candidate will be expected to have an outstanding background in medical image analysis, computer vision, machine learning and programming. The researcher will be a member of the Data Science Institute (DSI) and a member of the Biomedical Image Analysis Group (BioMedIA) based at the South Kensington Campus, Imperial College London, and will be supervised by Dr Wenjia Bai.
Duties and responsibilities
You will be expected to:
- plan research in accordance with the project aims;
- conduct research with appropriate supervision;
- develop novel algorithms for medical image analysis, machine learning and 3D shape analysis;
- curate a population-level database of cardiac shapes;
- present findings to colleagues and actively participate in group research meetings and internal seminars;
- submit publications to high-quality refereed journals and conferences;
- attend relevant conferences and workshops as necessary;
- assist in supervising undergraduate and postgraduate research students as required;
- and promote the reputation of the group, the departments and the College.
Essential requirements
To apply you should have a PhD* in a subject relevant to medical image analysis, computer science, electrical engineering or a closely related discipline, or equivalent research experience in:
- medical image analysis
- computer vision
- machine learning
*Candidates who have completed but not yet been officially awarded their PhD will be appointed as a Research Assistant.
You should have proven experience within a research environment and a track record of publications in relevant and refereed conferences/journals on medical image analysis, computer vision and machine learning, along with a strong interest in medical imaging and machine learning research.
Further Information
The position is full-time, starting on 1 July 2024, with a fixed term contract for 24 months in the first instance (with potential for extension).
Should you require any further details on the role, please contact Dr Wenjia Bai – , with [RA BHF New Horizons] in the subject of the email and your CV.
Candidates will need to complete an online application. For technical issues when applying online please email
Closing date: 3/06/2024
Apply online via the above 'Apply' button.
£45,593 to £47,376 per annum
