Leveraging probabilistic AI for heat-related health risk mitigation and adaptation
Background
With temperature records having been broken repeatedly in recent decades, heat-stress is posing a serious health risk (e.g. the fatalities in the 2007 London marathon). This project aims to quantify the spatially-and-temporally varying heat-risk in the UK and to understand how this is affected by climate change. The project will leverage probabilistic (Bayesian) AI methods for modelling weather and health data provided by the UK Met Office, plus access to operational weather forecasts and climate projections. The project is at the interface between AI, environmental science, meteorology and epidemiology. Skills such as machine learning, environmental and health data manipulation, risk mapping and decision making under uncertainty are expected to be gained by the student, who will have the chance to be hosted at the Met Office as a visiting scientist.
PhD opportunity
Other information
Applicant profile: This project would suit students with a strong background in mathematics/statistics/machine learning or other appropriate quantitative background, who want to apply these skills to environmental epidemiology and more generally the interface between climate change and health.
- https://www.metoffice.gov.uk/weather/warnings-and-advice/seasonal-advice/heat-health-alert-service
- https://www.metoffice.gov.uk/research/climate/climate-impacts/health