The post is an exciting opportunity for a researcher to develop novel statistical methods in causal inference and contribute to a strategic partnership between UCL, the University of Oxford, and Novo Nordisk. You will develop methodology to account for potential sources of disparity in treatment effect estimates between multiple data sources, including confounding, covariate shift, missing data, and measurement error. The goal will be to address each source of bias in turn before synthesizing these into a single framework for robust point estimation and valid inference. The postholder will implement these methodological advances into user-friendly software, including tutorials and best-practice guidelines, aimed at clinicians and biostatisticians.
The post is funded for 2 years and available from the 1st September 2026, though a later start is possible.
Salary:
The successful candidate must have a PhD in Statistics, Biostatistics, or a closely related quantitative discipline and strong programming skills in Python or R. They will also have experience in causal inference research, including methods for treatment effect estimation as well as experience in developing and evaluating novel statistical methodology.
As well as the exciting opportunities this role presents, we also offer some great benefits some of which are:
Visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits to find out more.
The department holds a Silver Athena SWAN award in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. We strongly support UCL's Equalities and Diversity Strategy and encourage applications to our vacancies from under-represented groups.
Tagged as: Life Sciences
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