Postdoctoral Researcher in Biostatistics - Statistical Machine Learning

We are seeking

to appoint a Postdoctoral Researcher to develop novel probabilistic statistical machine learning methods to build causal predictive models available in the one-of-a-kind Novartis-Oxford MS (NO.MS) dataset as part of Oxford–Novartis Collaboration for AI in Medicine. The NO.MS is the largest and the most comprehensive dataset on multiple sclerosis (MS), a collection of data on over 40,000 individuals measured longitudinally, some over a decade. Whilst you will be predominantly based at the Big Data Institute, you will also be expected to spend time at the Department of Statistics and participate in the OxCSML research group in Statistics. You will provide probabilistic machine learning expertise to the Oxford–Novartis Collaboration for AI in Medicine, contributing to the study design and analysis of data alongside the development and application of new analytical methods independently or in collaboration with others. This post will be a key part of the core Oxford analysis team working in collaboration with imaging specialists and other biostatistics and machine learning researchers to deliver optimal research for the collaboration. You will be responsible for the development, implementation, and evaluation of advanced causal and probabilistic statistical machine learning methodologies for individual-level outcome prediction and treatment response modelling. You will work with large-scale longitudinal clinical, laboratory, and high-dimensional neuroimaging data from the Oxford–Novartis Multiple Sclerosis (NO.MS) dataset to construct scalable prognostic and predictive models capable of handling missing data and heterogeneous data modalities. The role will involve close collaboration with clinicians, statisticians, and machine learning researchers, contributing to study design, statistical analysis plans, and the dissemination of findings through peer-reviewed publications, conference presentations, and internal scientific reports within the Oxford–Novartis Collaboration for AI in Medicine. It is essential that you hold a PhD/DPhil (or are close to completion) in Statistics, Biostatistics, Statistical Machine Learning, or a closely related quantitative discipline, with demonstrated expertise in statistical model development and algorithmic methodology, particularly within Bayesian or probabilistic frameworks. You must have strong knowledge of modern computational statistics, generative models, causal inference, and predictive modelling, alongside experience in implementing analytical methods using statistical software such as R or MATLAB and scripting languages including Python. The ability to communicate complex methodological concepts effectively and to work collaboratively within a multidisciplinary research environment is essential.