Research Associate in Statistical Methodology/Biostatistics

Job reference: SAE-031547

Salary: £37,694 - £46,049 per annum depending on experience

Faculty/Organisational Unit: Science and Engineering

Location: Oxford Road

Employment type: Fixed Term

Division/Team: Department of Mathematics

Hours Per Week: Full time (1 FTE)

Closing date (DD/MM/YYYY): 09/06/2026

Contract Duration: Fixed term for 32 months

School/Directorate: School of Natural Sciences

We are seeking a motivated and collaborative individual to join our team as a Postdoctoral Research Associate in Statistical Methodology / Biostatistics. This role offers an exciting opportunity to contribute to the NIHR-funded project “Joint Modeling for Dynamic Risk Prediction in Extreme Clinical Cases Using Longitudinal Patient Data” within the Department of Mathematics, School of Natural Sciences.

You will:

• Work with Dr. Taban Baghfalaki on Joint Modeling for Dynamic Risk Prediction in Extreme Clinical Cases Using Longitudinal Patient Data;
• Develop advanced statistical methodology for dynamic risk prediction using longitudinal patient data;
• Collaborate with interdisciplinary clinical and methodological research teams across the University and NIHR network;
• Develop reproducible statistical software, including R package development.

About you

Essential criteria

• A PhD or equivalent research experience in Statistics, Biostatistics, Data Science, or a closely related discipline, or expect shortly to obtain one;
• Research experience in an area of Statistics/Biostatistics of relevance to the project;
• A willingness and ability to learn rapidly any technical background knowledge required for the project which you do not already possess;
• Strong communication skills in written and spoken English;
• A personal commitment to equality, diversity, inclusion and accessibility, and a willingness to work with colleagues from diverse backgrounds.

Desirable criteria

• Research experience in longitudinal data analysis, survival analysis, or joint modelling;
• Experience in extreme value methods, quantile joint modelling, Bayesian methodology, and the analysis of large-scale (big data) datasets would be advantageous;
• Proficiency in developing reproducible statistical software, including R package development.

Our benefits include: Generous employer contribution pension, 29 days annual leave plus bank holidays, along with Christmas closure, Ride to work and EV car scheme available.