effects from longitudinal electronic health records, including dynamic treatment strategies, time-varying confounding, treatment-effect heterogeneity, missing data, competing risks and high-dimensional covariates. Research will sit at the interface of medical biostatistics, causal inference, semiparametric statistics and statistical machine learning, with the primary emphasis on developing new statistical methodology rather than simply applying existing methods
Research Areas
The project may include methodological development in:
- Target trial emulation
- Dynamic treatment regimes
- Semiparametric and nonparametric estimation
- Doubly robust and debiased machine learning
- Heterogeneous treatment effect estimation
- Longitudinal and survival analysis
- Propensity score methods and overlap weighting
- Transportability and generalisability
- Sensitivity analysis
- Reproducible statistical computing and open-source software
Methodological developments will be motivated by large-scale healthcare datasets, including electronic health records and other linked observational data resources.
Funding
The studentship includes:
- Fully funded 4-year Structured PhD
- €25,000 annual tax-free stipend
- EU tuition fee waiver
- Conference, workshop and specialist training support
- Computing resources and laptop provided
Candidate Profile
Applicants should hold (or expect to obtain) a First Class or Upper Second Class Honours degree (or equivalent) in Statistics, Biostatistics, Mathematics, Applied Mathematics, Data Science, Computer Science, Econometrics, Epidemiology or another closely related quantitative discipline.
Applicants should demonstrate:
- Strong mathematical and statistical ability
- Experience with statistical programming (preferably R)
- Interest in statistical methodology, causal inference and machine learning
- Excellent communication and problem-solving skills
An MSc and experience in causal inference, longitudinal data analysis or survival analysis are desirable but not essential.
The successful candidate will join an interdisciplinary research environment with opportunities to publish in leading journals, present at international conferences, attend specialist workshops and develop open-source statistical software. Primary Supervisor: Dr Maurice O'Connell, Associate Professor in Medical Biostatistics, School of Medicine, University of Limerick
Applications
Applications should include a cover letter, CV, academic transcripts and contact details for two academic referees. Applications will be reviewed on a rolling basis until the position is filled.
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