Senior Researcher in Healthcare AI and Machine Learning

at  University of Oxford

We are seeking a creative and enthusiastic senior researcher with expertise in state-of-the-art machine learning to work in a large and successful research group based at the University of Oxford’s Big Data Institute. We are focused on analysing healthcare data, improve the diagnosis and treatment of infections and other serious illnesses, as well as developing predictive and generative AI tools to improve run hospitals better.
You will be a central and really valued part of our research group and responsible for delivering new and exciting machine learning-based analyses of multimodal healthcare data. Extensive deidentified electronic healthcare data records are available from hospitals in Oxfordshire and elsewhere in the UK. You will have opportunities to apply a wide variety of approaches including Large Language Models, Transformer based analyses of complex time series, and Foundational models for simultaneously undertaking multiple healthcare tasks.
You will also be responsible for identifying opportunities for novel applications of new machine learning to healthcare data. We are particularly interested in approaches that that are readily updatable over time and to new contexts, and that quantify the uncertainty in predictions made. There will also be opportunities for taking part in evaluating high performing tools in real-world healthcare settings.
Academic oversight and supervision will be provided by Professor David Eyre (https://www.bdi.ox.ac.uk/Team/david-eyre). Oxford Population Health (Nuffield Department of Population Health) contains world-renowned population health research groups and provides an excellent environment for multi-disciplinary research and teaching. Oxford Population Health is a key partner in the Big Data Institute (BDI), contains world-renowned population health research groups, and is an excellent environment for multi-disciplinary teaching and research.
To be considered you will hold a PhD in relevant scientific subject. Strong experience, ability and practical success in machine learning and statistics as well as proficiency in the use of programming languages and statistical analyses are essential for this post. Previous research experience applying machine learning methods to large-scale healthcare data would be desirable.
The post is full-time (although part-time is considered) and fixed term to 31 March 2026. The closing date for applications is noon on Friday 14 June 2024.
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

Please refer the Job description for details