Fully Funded PhD in Statistics, Causal Inference and Machine Learning

Project Overview Applications are invited for a fully funded PhD in Statistics, Causal Inference and Machine Learning at the University of Limerick. The project focuses on developing novel statistical methodology for estimating causal treatment effects from longitudinal electronic health records and observational healthcare data. A central challenge in modern health data science is the estimation of treatment effects in the presence of: dynamic treatment strategies time-varying confounding treatment-effect heterogeneity limited treatment overlap high-dimensional longitudinal data structures competing risks and complex survival outcomes The primary focus of this PhD is methodological innovation in causal inference, semiparametric statistics, and statistical machine learning, with applications motivated by important healthcare problems in multimorbidity, polypharmacy, and chronic disease management. Research Themes The PhD will develop methods in areas including: Causal inference from observational healthcare data Target trial emulation Dynamic treatment regimes Semiparametric and nonparametric estimation Doubly robust and efficient estimation methods Debiased / double machine learning Heterogeneous treatment effect estimation Longitudinal data analysis Survival analysis and competing risks Propensity score methods and overlap weighting Transportability and generalisability Sensitivity analysis and robustness Reproducible statistical computing and open-source software development The precise methodological direction will be refined during the PhD in line with emerging research developments and the candidate’s interests. Research Areas Causal Inference Semiparametric Statistics Machine Learning for Causal Inference Target Trial Emulation Dynamic Treatment Regimes Longitudinal Data Analysis Survival Analysis Health Data Science Electronic Health Records Data Sources The project will involve analysis of large-scale healthcare datasets, including (subject to access and approval): UK Biobank Longitudinal electronic health records Linked routine healthcare datasets Population-based cohort studies Simulated data Applications may include: medication optimisation deprescribing strategies cardiovascular disease prevention diabetes management mental health interventions cancer prevention and screening clinical decision support palliative care Training and Research Environment The successful candidate will join an interdisciplinary research environment within the School of Medicine at the University of Limerick. Training will be provided in: Modern causal inference and statistical learning Semiparametric and high-dimensional statistics Longitudinal and survival data analysis Scientific computing and reproducible research Academic writing and research communication The candidate will be supported and encouraged to: publish in leading journals in statistics, biostatistics, epidemiology, and machine learning present at international conferences attend specialist workshops and summer schools develop open-source software tools This project offers the opportunity to develop cutting-edge statistical methodology at the interface of causal inference, machine learning, and healthcare decision-making. The successful candidate will work on open methodological questions, contribute to open-source software, publish in leading international journals, and collaborate across statistics, medicine, and health data science. Supervision Dr Maurice O’Connell Associate Professor in Medical Biostatistics School of Medicine University of Limerick Additional methodological and clinical collaborators may contribute to supervision and training. Candidate Profile Applicants should hold, or expect to obtain before September 2026, a First Class or Upper Second Class Honours degree (or international equivalent) in a quantitative discipline such as: Statistics Biostatistics Mathematics Applied Mathematics Data Science Computer Science Econometrics Epidemiology or a closely related field Essential Requirements Strong quantitative and statistical background Experience with statistical programming (preferably R) Strong interest in causal inference and statistical methodology Excellent communication skills Ability to work independently and collaboratively Desirable MSc in a relevant discipline Experience with observational or longitudinal data Familiarity with causal inference or machine learning methods Knowledge of survival analysis or time-to-event modelling Interest in reproducible research and open-source development Application Procedure Applicants should submit a single PDF containing: Cover letter outlining motivation and research interests Curriculum vitae (CV) Academic transcripts Contact details for at least two academic referees Applications will be reviewed on a rolling basis until the position is filled. Informal Enquiries Informal enquiries are welcome: Dr Maurice O’Connell School of Medicine, University of Limerick Email: maurice.oconnell@ul.ie Application Outcome Only shortlisted candidates will be contacted.