PhD Opportunities in Pharmacoepidemiology & Ageing Research
Not stated
- Funding
- Self-Funded PhD Students Only
- Application deadline
- Year-round applications
About the project
About the Project About the Project We are inviting applications from highly motivated candidates for self-funded PhD positions examining the impact of anticholinergic medications on mobility, functional decline, and multimorbidity in ageing populations. With rapidly ageing societies, understanding how commonly prescribed medicines influence physical function, cognition, and health outcomes is critical. Anticholinergic burden has been associated with falls, frailty, hospitalisation, and mortality — yet its longitudinal impact on mobility trajectories and biological ageing remains insufficiently understood. This PhD will leverage large-scale, internationally recognised longitudinal datasets including: ELSA (English Longitudinal Study of Ageing) TILDA (The Irish Longitudinal Study on Ageing) interRAI datasets UK Biobank Core Research Themes Applicants may focus on one or more of the following themes: Anticholinergic Medications and Mobility Decline Longitudinal modelling of gait speed, grip strength, balance, and frailty progression Time-to-event modelling of mobility disability Medication burden trajectories and functional outcomes Sex- and age-specific effects Anticholinergic Burden and Multimorbidity Clusters Identification of biomarker and disease clusters Machine learning–derived medication burden scores Interaction between inflammation markers and medication exposure Medication Use and Biological Ageing Inflammatory biomarkers (CRP, IL-6, etc) Drug Safety & Functional Outcomes in Real-World Data Comparative safety analyses Cross-country comparisons (UK, NZ, international datasets) Methodological Approaches Candidates will gain knowledge of analytical techniques, including: Longitudinal mixed-effects modelling Cox proportional hazards modelling Competing risk models Propensity score methods Machine learning (elastic net, random forests, neural networks) Cluster and network analyses Causal inference frameworks Strong emphasis will be placed on reproducible research using R and/or Python. Candidate Profile We welcome applicants with: A Master’s degree (or equivalent) in Pharmacy, Epidemiology, Public Health, Statistics, Medicine, Data Science, or related discipline Strong quantitative skills Experience in R, Python, or Stata Interest in ageing research, medication safety, and multimorbidity Motivation to publish in high-impact journals What We Offer Access to world-leading longitudinal ageing datasets Supervision within an established pharmacoepidemiology research group Training in advanced statistical and AI methods Opportunities for international collaboration Conference presentation opportunities Support for academic career development Impact This research directly informs: Safer prescribing in older adults Deprescribing guidelines Clinical decision support systems Policy recommendations for ageing populations Graduates will be well-positioned for careers in academia, regulatory science, clinical research, or data science. Funding Positions may be: Self-funded Sponsored candidates (international applicants welcome) Applicants are also encouraged to apply for competitive scholarships.