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Research Assistant – Affordable Artificial Intelligence for Medical Imaging

University of Oxford - Oxford Population Health (Nuffield Department of Population Health, University of Oxford)

Location: Oxford
Salary: £32,332 to £38,205 per annum (including Oxford Weighting Allowance)
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 16th June 2025
Closes: 11th July 2025
Job Ref: 171998
The Nuffield Department of Population Health (NDPH) contains world renowned population health research groups and provides an excellent environment for multi-disciplinary research and teaching.
 
We are seeking a Research Assistant to join a team working at the intersection of medical imaging and machine learning at the University of Oxford. This is an exciting opportunity to work across disciplines of global health, cardiovascular diseases, inequality in access to imaging and AI-powered diagnosis.
 
The successful candidate will contribute to a project that integrates cutting-edge AI techniques, such as medical image analysis and natural language processing, with applications in cardiology within a global context. You will be responsible for the design and testing of bespoke AI models for cardiac imaging, as well as contributing to their clinical validation and real-world translation. These models aim to support non-specialist healthcare workers and address critical skill shortages in cardiac diagnostics, particularly in low-resource settings.
 
In the long term, this project seeks to advance digital health equity by empowering healthcare providers in underserved regions and providing a testbed for the responsible deployment of AI in clinical environments.
 
To be considered, you must hold a Masters degree in engineering, mathematics or computational and have demonstrated experience in programming (Python preferably) for medical imaging processing and machine learning. You are flexible, pro-active and an adaptable team worker.
 
This is a full time, fixed term post (part time considered) for 12 months.  
 
The closing date for applications is noon on 11 July 2025.
 
You will be required to upload a CV and a cover letter as part of your online application. The cover letter should clearly describe how you meet each of the selection criteria listed in the job description.
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