Developing Novel Methods for Causal Inference Using Healthcare Data
Applications are especially encouraged from students interested in statistical methodology, causal inference, semiparametric statistics, machine learning, and health data science.
September 2026
Fully funded 4-year Structured PhD
€25,000 annual tax-free stipend
EU tuition fees covered
Conference, training and workshop support
Conference and training support
Laptop provided
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.
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.
Further Information
Link to EURAXESS advertisement: https://euraxess.ec.europa.eu/jobs/445195