Oxford Population Health (the Nuffield Department of Population Health) provides an excellent environment for multi-disciplinary research and teaching and for professional and support staff. We work together to answer some of the most important questions about the causes, prevention and treatment of disease.
We are seeking to appoint a Postdoctoral Researcher in Biomedical Image Analysis to join the Oxford-Uganda Collaboration on Schistosomiasis, an internationally recognised partnership between the University of Oxford and the Uganda Ministry of Health. This is an exciting opportunity to contribute to a large-scale, interdisciplinary research programme.
We are looking for someone with proven expertise in a fast-paced environment, who is committed to delivering high-quality research support and innovation in global health. You will work as part of the SchistoTrack team, a prospective cohort study that investigates predictive factors for schistosomiasis-associated morbidities across rural Ugandan communities bordering the West Nile, Lake Albert, and Lake Victoria.
To be considered for the role, you should hold (or be close to completion of) a PhD/DPhil in Health Data Science, along with relevant experience in machine learning and image analysis for ultrasound images and video. The successful applicant will possess specialist experience conducting fieldwork, particularly in low-resource or rural settings. This role requires the ability to independently manage academic research and its associated activities, and a track record of contributing to academic publications and/or conference presentations.
This role is based in Oxford and offered on a full-time basis (part time considered). It is a fixed term post for 1.5 years in the first instance.
The closing date for applications is noon on 01 October 2025.
You will be required to upload a CV and Supporting Statement as part of your online application. The Supporting Statement should include a cover letter and should also clearly describe how you meet each of the selection criteria listed in the job description.