The School of Mathematics welcomes applications for a research fellowship in statistics to work on the UKRI Future Leaders Fellowship project ‘Computational Statistics to Tackle Modern Slavery’, led by Dr Rowland Seymour. The successful candidate will join a diverse and friendly research group with PhD students and a Research Software Engineer.
The goal of the project is to develop computational statistical methods to estimate the prevalence of modern slavery. We will then use these methods with partners in the law enforcement and third sectors to understand how modern slavery can be tackled. A video describing the project can be viewed here: https://www.youtube.com/watch?v=IzPuuBnrIDc. The successful candidate will be developing Bayesian models for estimating the prevalence and risk of modern slavery. There will be a focus on Bayesian nonparametric methods and practical development of MCMC algorithms that can be applied to data. Translating the project findings into meaningful policy decisions will also be an important part of the project. Policy makers at local at national levels will be involved in the project, as well as partners in the law enforcement and third sectors.
The post is available for a period of 2.5 years. The starting date is 1st September 2025 (with some flexibility). The successful applicant will have access to generous travel funding to support dissemination of the project findings.
Role Summary
- Conduct original research within the research project
- Disseminate research findings through publications, seminars/presentations etc
- Work within specified research grants and projects and contribute to writing bids
- Operate within area of specialism
- Analyse and interpret research findings and results
Main Duties
The responsibilities may include some but not all of the responsibilities outlined below.
- Develop research on statistical models and Bayesian inference methods for implementing them
- Contribute to writing bids for research funding
- Analyse and interpret data
- Work with external partners to facilitate impact and knowledge exchange
- Apply knowledge in a way which develops new intellectual understanding
- Disseminate research findings for publication, research seminars etc
Person Specification
- Hold or be close to obtaining a PhD or equivalent qualification(s) in Statistics, Applied Statistics, Computational Statistics or related areas
- Track record of strong original research contributions in applied statistics, computational statistics, or related areas, including publications in leading subject-specific journals within that field
- High level analytical capability
- Ability to communicate complex information clearly
- Fluency in relevant models, techniques or methods and ability to contribute to developing new ones
Informal enquiries to Rowland Seymour, email: r.g.seymour@bham.ac.uk and Dr Panayiota Touloupou, email: p.touloupou@bham.ac.uk
To download the full job description and details of this position and submit an electronic application online please click on the above 'Apply' button
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