About the Project
Background
Climate change does not put everyone in the same danger. Whether a heatwave, flood or drought becomes a disaster depends on where the hazard lands and on who and what is exposed. Answering “where is risk worst, and for whom?” means pulling together data that was never meant to be combined: climate projections, satellite records, census and economic statistics, health data, and text from policy documents and news. Each is patchy, measured differently, and uncertain. Researchers use data science…
(machine learning, text mining, data fusion) to turn these fragments into comparable risk indicators, and decision science (multi-criteria analysis, preference elicitation) to weigh them into a picture that reflects what people care about. National risk portals and composite indices exist, but they tend to bury their assumptions, treat uncertain inputs as exact, and give users little to interrogate. The open problem is making climate risk assessment transparent, uncertainty-aware and usable.
PhD project
This PhD builds both the methods and a working decision tool to answer a deceptively simple question: as the climate changes, who is most at risk, and how confident can we be? The student picks one sector and question early on, for example urban heat, agricultural drought, flood exposure, climate-linked migration or infrastructure resilience, and co-develops the project from there.
Three linked challenges run through it. Data: find and pull together open sources that do not agree on units, resolution or coverage, and use web scraping, text mining, geospatial processing and data fusion to convert them into quantified risk indicators, carrying the uncertainty in each rather than discarding it. Integration: apply multi-criteria decision analysis and preference elicitation to combine indicators into a composite risk score, and stress-test how the ranking of high-risk places shifts under different weightings and under input uncertainty, so the result is honest about what it does and does not know. Tool-building: design an interactive geospatial dashboard that lets a non-technical user see why a place scores as it does, change assumptions, and compare scenarios.
The project connects two UNRISK themes, data science and decisions/communication, and is co-supervised by Dr Andrea Taylor, whose work on how people perceive and act on climate and weather risk will shape the elicitation and the dashboard. There is scope to work with an operational or policy partner.
The student leaves with reusable methods for uncertainty-aware risk aggregation, an open-source decision-support tool, and evidence on how weighting and uncertainty change which places count as most at risk, plus skills spanning data engineering, decision modelling and stakeholder work.
Applicant Profile
Applicants with a strong quantitative background, in statistics, data science, engineering, computer science or similar, who want to point those skills at climate and environmental risk. You should be happy programming (for example Python or R), wrangling and joining messy data from many sources, dealing with missing values, and building interactive tools/dashboards. No prior climate or decision science is expected; curiosity about working across disciplines, and about getting tools into the hands of decision makers, matters more. Training needs are planned with you in the first year.
Funding Notes
This project is part of the UNRISK CDT, which offers 15-18 fully-funded NERC studentships, covering full university tuition fees; a personal stipend at standard UKRI rates; £6000 individual research and training costs; £5000 (per student) of cohort-level training; and a ‘Flexible Fund’ for special projects.
International applicants will need to cover costs related to applying for a student visa and the international health surcharge (IHS)
Applications are open to UK and international applicants. The number of awards for international applicants is limited by UKRI rules.
More information is available on the UNRISK website: View Website
References
– Centre for Decision Research, University of Leeds (the supervisors’ research group; decision science for climate and risk): https://cdr.leeds.ac.uk/
– Climate Just – a UK map tool showing how social vulnerability and hazard exposure combine into “climate disadvantage” at neighbourhood scale; this PhD pushes that idea further, across sectors and with uncertainty made explicit: https://www.climatejust.org.uk/mapping
– IPCC Sixth Assessment Report, “The concept of risk” – the hazard, exposure and vulnerability framing the project builds on (short note): https://www.ipcc.ch/site/assets/uploads/2021/01/The-concept-of-risk-in-the-IPCC-Sixth-Assessment-Report.pdf
Project supervisors
Dr Sajid Siraj
Dr Sajid Siraj holds a PhD in Computer Science from the University of Manchester, United Kingdom. He also earned an MSc in Embedded Systems from the same institution and a B.E. in Electrical Engineering from the National University of Sciences and Technology in Pakistan. Dr Siraj is currently an Associate Professor at the University of Leeds, where he serves as the Program Director for the MSc Business Analytics & Decision Sciences and is the EDI Chair for the Data Scientists Development Programme. His research interests encompass decision support systems, explainable artificial intelligence, machine learning, data and text mining, and multi-criteria decision analysis. Dr Siraj has engaged in various projects involving text analytics, dominance-based rough sets analysis, imbalanced classification, and visual aids, applying his expertise to fields such as seismic data processing and telecommunications.
Dr Andrea Taylor
Dr Andrea Taylor holds joint posts at Leeds University Business School and the School of Earth and Environment. She has a background in cognitive psychology and is a behavioural decision researcher with over a decade of experience in teaching in higher education. Dr Taylor’s research interests encompass risk perception and communication, climate and weather risk preparedness, and expert judgement. Her work primarily focuses on applying insights and methodologies from the behavioural sciences to tackle communication challenges in providing climate and weather information services, as well as supporting decision-making under uncertainty. To address these challenges, she collaborates with experts across various disciplines, including climatology, meteorology, environmental science, health economics, and risk management. Current research projects include examining public responses to severe weather warnings in the UK, developing weather forecasting science and services in West and East Africa, creating climate information tools for water resource management, and enhancing the communication of uncertainty in warning systems.