Spatial Association Modelling for Predicting and Forecasting Hazard Risks
This PhD project, 'Spatial Association Modelling for Predicting and Forecasting Hazard Risks', is offered at The University of Manchester within the Department of Mathematics. The research focuses on understanding and predicting climate-led hazards, which cluster and propagate across landscapes, communities, and infrastructure networks. Spatial association—the statistical relationship between events in one location and those nearby—is fundamental to forecasting risks and issuing timely warnings.
The successful candidate will develop advanced mathematical and statistical modelling frameworks to capture the spatial behaviour of climate-induced hazards and the interdependence of climatic variables across space. The project integrates spatial statistics, geospatial data science, and risk modelling to advance detection of emerging hotspots, understand cascading hazard pathways, and improve predictive models for multihazard risk. The research is part of the Informatics for Multi-hazard Risk and Resilience (i-Risk) NERC Doctoral Focal Awards (DFA), which aims to train the next generation of research practitioners and leaders in informatics and risk resilience.
i-Risk builds on the strengths of four leading UK institutions, offering unparalleled facilities and support from over 70 multidisciplinary academic supervisors. Doctoral researchers will undertake structured training and interdisciplinary research, collaborating with industry, government agencies, global organisations (such as the United Nations), and NGOs to ensure research informs policy and practice. The four core research themes are: observations, monitoring and understanding; modelling and understanding processes/risk; forecasting, prediction and early warning; and risk communication and management solutions.
Eligibility requires an excellent academic record (UK First-class or 2.1 honours or international equivalent) in Mathematics, Engineering, Earth Sciences, Computing, or related physical science disciplines (MSc, MSci or BSc). Applicants must have a strong quantitative background in applied mathematics, physics, engineering, or related fields, and be confident in R or other mathematical programming. English language certificate is required if applicable.
The 3.5-year PhD studentship is funded by the NERC i-Risk DFA, open to Home (UK) and overseas students. The successful candidate will receive an annual tax-free stipend at the UKRI rate (£21,805 for 2026/27, subject to annual uplift), and tuition fees will be paid. The stipend is expected to increase each year. The start date is October 2026.
Applicants must submit an online application via the University of Manchester portal, quoting advert reference IRISK-26-UOM05. Required documents include a two-page personal statement (addressing research interests and specific questions), CV, academic transcripts, degree certificates, interim transcript (if in progress), and contact details for two referees (with official university/work email addresses). A supporting statement outlining motivation, relevant experience, and skills is mandatory. Incomplete applications will not be considered. Interviews are anticipated to be held remotely via Microsoft Teams week commencing 29 June 2026.
For project-specific queries, applicants are encouraged to contact potential supervisors by email. General questions can be sent to [email protected], and technical questions about the application process to [email protected]. Further details about i-Risk can be found at https://github.com/i-risk-dfa.
This opportunity is ideal for candidates interested in spatial statistics, climate science, risk modelling, and informatics, seeking to contribute to innovative research with real-world impact on hazard risk resilience and sustainability.
