Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling Full-time

Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling

Big Data Institute, Li Ka Shing Centre for Health and Information Discovery, Old Road Campus, Headington, Oxford, OX3 7LF Additional location: Department of Statistics, 24-29 St Giles', Oxford, OX1 3LB

We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models including conditional diffusion and flow matching models for synthesising Magnetic Resonance Imaging (MRI) and predictive analysis. This work will focus on the unique Novartis Oxford MS (NO.MS) dataset, the largest and most comprehensive dataset on multiple sclerosis (MS), encompassing longitudinal data from over 40,000 individuals, some tracked for more than a decade.

You will be responsible for advancing and applying state-of-the-art probabilistic deep generative models, including conditional diffusion and flow matching approaches, to generate advanced MRI modalities from conventional clinical scans. You will also develop predictive models capable of characterising disease progression and forecasting individual outcomes in multiple sclerosis under different treatment exposures. Beyond your own research, you will contribute to the design and delivery of collaborative projects, working closely with clinicians, imaging experts, and computational scientists across the Oxford–Novartis Collaboration for AI in Medicine. This will involve planning and managing your own programme of work, advising on model development strategies, finalising statistical analysis plans, and ensuring the timely completion of high-quality data analyses. You will also be expected to publish your findings in leading peer-reviewed journals, present your work at national and international conferences, and engage actively in seminars and collaborative discussions.

You must hold a PhD/DPhil in Statistics, Statistical Machine Learning, Deep Generative Modelling, or a closely related field, together with relevant postdoctoral research experience. You will bring extensive expertise in the development and application of conditional diffusion models, flow matching techniques, or related generative approaches, as well as experience working with high-throughput data in the context of human disease. Strong programming skills are essential, particularly in Python, R, or MATLAB, alongside familiarity with Bayesian methods and statistical modelling. A proven record of publishing in high-quality journals and presenting at scientific meetings will be required, demonstrating your ability to lead and deliver impactful research.

Applications for this vacancy should be made online and you will need to upload a supporting statement and CV. Your supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. Please restrict your documentation to your CV and supporting statement only. Any other documents will be requested at a later date.

This position is offered full time on a fixed term contract until 31 August 2027 with possibility of extension and is funded by Novartis. Only applications received before 12 midday on Monday 17 August 2026 will be considered. Please quote 182346 on all correspondence.