This is a Fixed Term contract until 31st May 2028 working 21 hours per week. We are looking for a Senior Research Fellow in Statistics to advance the dynamic research portfolio of the Population Data Science group (https://popdatasci.swan.ac.uk/) at Swansea University Medical School. The successful applicant will lead the development and application of advanced analysis methods utilising the rich linked-data environment at Swansea University to deliver high-impact research of public health and policy relevance. The post holder will be based in the Statistics Team, working closely with senior researchers nationally and internationally under the leadership of Professor Rhiannon Owen. The Population Data Science group is home to leading researchers, data scientists and statisticians who focus on making the best use of large-scale multi-dimensional data to improve the lives of the population. Our team of experts develop cutting-edge analytical tools and methodologies to link and analyse administrative, environmental, and health (including biological, clinical and genomic) data to address the most pressing health research challenges. The advanced analytics team specialise in the development and application of statistical methodology (including Bayesian methods, advanced survival analysis and causal inference) to utilise this data to address complex health policy questions. As part of the Population Data Science group, the post holder will be supported in undertaking innovative and impactful research, engaging with national and international partners and stakeholders, and continuing professional development through advancing skill sets and strategic expertise. Applications are sought from individuals with a national or international reputation in the development and application of methods for the analysis of large scale-data (including evidence synthesis) with a background in any of the following areas: statistics, mathematics, operational research, or related data science disciplines with a significant advanced analytical component. Whilst specialisations are flexible, alignment with the research interests of the Population Data Science group is required.