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Big Data Institute, Li Ka Shing Centre for Health and Information Discovery, Old Road Campus, Headington, Oxford, OX3 7LF

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"Senior Postdoctoral Researcher in Biostatistics: Statistical Machine Learning"

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Senior Postdoctoral Researcher in Biostatistics: Statistical Machine Learning

Research Grade 8

16 February 2026, 12:00 midday

Location

Oxford, UK (Big Data Institute, OX3 7LF & Dept of Statistics, OX1 3LB)

University of Oxford

Type

Full-time, Fixed-term until 31 August 2027

Salary

£49,119 - £58,265 per annum (incl. £1,730 Oxford Weighting)

Required Qualifications

PhD/DPhil in Statistics, Biostatistics or Statistical Machine Learning
Postdoctoral experience & publication record
Bayesian/probabilistic machine learning
Causal inference & prognostic modelling
R, MATLAB, Python programming
Scientific leadership

Research Areas

Biostatistics
Statistical Machine Learning
Causal Predictive Models
Multiple Sclerosis (NO.MS dataset)
Neuroimaging & MRI analysis
Individualized Treatment Effects
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Senior Postdoctoral Researcher in Biostatistics: Statistical Machine Learning

Senior Postdoctoral Researcher in Biostatistics: Statistical Machine Learning

Location: 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 looking to appoint a Senior 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.

Under the line management of Dr. Habib Ganjgahi and close collaboration with Professors Chris Holmes and Thomas Nichols, you will apply and develop state of the art causal scalable statistical machine learning prognostic models to identify factors and early change-parameters in clinical and MRI images that, on an individual patient level, contribute to a reliable prediction of time to long-term outcomes using clinical, laboratory and high-dimensional image data that can handle missing data and different data modalities and building individual treatment response models to predict which subjects will respond to treatment and heterogenous treatment effect.

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 be responsible for providing senior scientific leadership in the development, theoretical advancement, and application of state-of-the-art causal and probabilistic statistical machine learning methodologies for individual-level outcome prediction and treatment response modelling. You will lead methodological innovation using large-scale longitudinal clinical, laboratory, and high-dimensional neuroimaging data from the Oxford–Novartis Multiple Sclerosis (NO.MS) dataset, designing scalable predictive frameworks that explicitly address missingness, multimodal data integration, and heterogeneous treatment effects. You will play a central role in shaping statistical strategy within the Oxford–Novartis Collaboration for AI in Medicine, lead the formulation of statistical analysis plans, drive the production of high-impact peer-reviewed publications, and provide intellectual leadership in the supervision and mentoring of junior researchers and doctoral students.

It is essential that you hold a PhD/DPhil in Statistics, Biostatistics, Statistical Machine Learning, or a closely related quantitative discipline, with substantial postdoctoral research experience and an established publication record in leading peer-reviewed journals. You must demonstrate advanced expertise in the development of statistical models and algorithms, particularly within Bayesian, generative, or probabilistic machine learning frameworks, together with deep knowledge of causal inference, prognostic modelling, and individualized treatment effect estimation. Extensive experience in implementing and validating complex models using statistical software such as R or MATLAB and programming languages including Python is required. You should also have a proven ability to provide scientific leadership, contribute to the development of competitive research funding applications, articulate complex methodological concepts to diverse scientific audiences, and work effectively across disciplinary boundaries.

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 and is funded by Novartis.

Only applications received before 12 midday on 16 February 2026 will be considered. Please quote 184573 on all correspondence.

Contact Person: Bogdan Tiritelnicu
Vacancy ID: 184573
Closing Date & Time: 16-Feb-2026 12:00
Pay Scale: RESEARCH GRADE 8
Contact Email: recruitment@ndm.ox.ac.uk
Salary: Research Grade 8: Salary in range £49,119 - £58,265 per annum. This is inclusive of a pensionable Oxford University Weighting of £1,730 per year.

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Frequently Asked Questions

🎓What qualifications are required for this Senior Postdoctoral Researcher role?

You must hold a PhD/DPhil in Statistics, Biostatistics, Statistical Machine Learning, or related field, with substantial postdoctoral experience and publications in top journals. Essential skills include expertise in Bayesian, generative, probabilistic machine learning, causal inference, prognostic modelling, and tools like R, MATLAB, Python. Leadership in research and cross-disciplinary collaboration is key. Review academic CV tips for applications.

🔬What are the main responsibilities in this Biostatistics postdoc position?

Lead development of causal scalable statistical machine learning models using the NO.MS dataset for MS outcome prediction and treatment response. Handle multimodal data (clinical, MRI), missing data, and heterogeneous effects. Provide scientific leadership, mentor juniors, author publications, and shape analysis plans in the Oxford–Novartis Collaboration. Explore postdoc success strategies.

💰What is the salary, contract duration, and location for this job?

Salary: Research Grade 8: £49,119 - £58,265 p.a. (incl. pensionable Oxford Weighting). Full-time fixed-term contract until 31 August 2027, funded by Novartis. Primarily at Big Data Institute, Oxford OX3 7LF, with time at Department of Statistics, OX1 3LB. Check postdoc jobs for similar roles.

📝How do I apply for this Statistical Machine Learning postdoc at Oxford?

Apply online via University of Oxford portal with CV and supporting statement addressing selection criteria. Quote Vacancy ID: 184573. Deadline: 16 February 2026, 12:00 midday. Email: recruitment@ndm.ox.ac.uk. Limit to CV/supporting statement. See research role advice (adaptable globally).

🧠What research areas does this role focus on at University of Oxford?

Develop probabilistic statistical machine learning for causal models in multiple sclerosis using the largest NO.MS dataset (40,000+ patients). Integrate clinical, lab, high-dimensional MRI neuroimaging data for individual predictions and treatment effects. Join OxCSML group. Related: research jobs in biostatistics.

🌍Is visa sponsorship available for international applicants?

Visa sponsorship is not explicitly mentioned; UK visas depend on eligibility. Experienced researchers may qualify under Skilled Worker route. Confirm with recruitment@ndm.ox.ac.uk. Explore UK postdoc opportunities for internationals.
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