Funded PhD in Comparative Epidemiology and Biomodelling of Mycobacterium bovis at University College Dublin University College Dublin in Ireland

Funded PhD opportunity at University College Dublin (Ireland) in comparative epidemiology and biomodelling, focused on the transmission, diagnosis, and control of Mycobacterium bovis (bovine tuberculosis) in Northern Ireland and the Republic of Ireland.

The project sits within the UCD School of Veterinary Medicine and the UCD School of Mathematics and Statistics, and is supervised by Dr Miriam Casey and Dr Michael Fop. It is a strong fit for students interested in veterinary epidemiology, infectious disease modelling, statistical modelling, One Health, and interdisciplinary work linking animal health, policy, and data analysis.

Research focus: developing dynamic transmission models for bovine TB, analysing veterinary epidemiological data, comparing health systems and control policies across two countries, and working with government and research stakeholders to understand and reduce disease spread.

Eligibility highlights: applicants should have or expect a 2:1 honours degree; a relevant Master’s degree is desirable. Backgrounds in biological/veterinary sciences, medicine, ecology, agricultural science, statistics, mathematics, applied mathematics, computer science, or related STEM fields are welcome. Strong quantitative ability, programming skills in Python or R, and proficiency in statistical modelling are important. English language competence is required where applicable, and good interpersonal skills/adaptability are valued.

Funding: fully funded for 4 years, with an annual tax-free stipend of about €25,000, tuition fee coverage, and extra support for training, travel, and equipment.

Application window: deadline is 29 April 2026, with a September 2026 start date.

How to apply: email Dr Miriam Casey with a CV, academic transcripts, and a short statement of purpose/cover letter. Include two academic referees and use the subject line: PhD application - bTB cross-border modelling project.