EPSRC Project Proposals 2026/27 - Next-Generation Farrington Model for Infection Prevention and Control: An Enhanced Farrington Algorithm with Spatiotemporal and Adaptive Baseline Capa
Core
Developing new statistical methods for detecting unusual patterns in healthcare-associated infections by enhancing the Farrington algorithm with spatiotemporal and adaptive baseline capabilities.
Role type
PhD researcher in statistical epidemiology
Builds
Next-generation outbreak-detection tools for Infection Prevention and Control teams
Domain
Public health, epidemiology, and statistical methodology
Deliverable
production ML models
Required skills
statistical modelling, mathematical analysis, programming in R or Python, simulation design, data analysis
Preferred skills
deep learning, computer graphics, knowledge of infectious disease data, experience with healthcare systems
Technologies
R, Python
Responsibilities
Develop flexible statistical models for infection surveillance, apply new models to real data from Northern Ireland, collaborate with Public Health Agency staff (nurses, epidemiologists, microbiologists), present work at conferences and publish in peer-reviewed journals
Seniority
PhD candidate