Publisher
source

Ce Zhang

Top university

11 months ago

From Hazards to Risk: Physics-Informed AI and SWOT Data for Global Flood Mapping and Socio-Economic Vulnerability University of Bristol in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD Project (Students Worldwide)

Deadline

Expired

Country flag

Country

United Kingdom

University

University of Bristol

Suggested positions

Publisher
source

University of Leeds

Country flag

United Kingdom

PhD opportunity at the University of Leeds on climate uncertainty, compound events, and water-system impacts in Eastern England . This project sits within the UNRISK CDT and focuses on how compound climate events and High Impact Low Likelihood (HILL) events interact with natural and human water systems. The research combines climate science , hydrology , environmental engineering , data analysis , data science , mathematical modelling , and decision making under uncertainty to improve climate ri...

Computer Science
Data Science
Environmental Science
+7 more

3 weeks ago

Publisher
source

University of Michigan

Country flag

United States

The University of Michigan School for Environment and Sustainability (SEAS) and Dr. Tiantian Yang’s research lab are recruiting a Postdoctoral Research Fellow in Hydrology and Water Resources at the Ann Arbor Campus, United States. This postdoctoral opportunity focuses on advanced research in hydrologic modeling , flood forecasting , extreme weather prediction , snow observation , snow modeling , soil moisture data analytics , and global reservoir/lake system analysis . The role also includes mo...

Computer Science
Data Science
Environmental Science
+10 more

3 days ago

Publisher
source

University of East Anglia

Country flag

United Kingdom

PhD opportunity at the University of East Anglia (Norwich, United Kingdom) in Artificial Intelligence , Computer Vision , Machine Learning , Remote Sensing , Data Science , and Environmental Science . This funded PhD project, supervised by Dr M Mackiewicz in the School of Computing Sciences, focuses on multispectral and hyperspectral imaging for the aerial detection and monitoring of marine litter . The project aims to improve automated classification and quantification of litter materials using...

Computer Science
Data Science
Environmental Science
+11 more

2 weeks ago

Publisher
source

Simon Gosling

University of Birmingham

Country flag

United Kingdom

PhD opportunity on AI and UK water security at the University of Birmingham , advertised by Professor Simon Gosling with collaborators Shasha Han (School of Geography, Earth and Environmental Sciences, University of Birmingham), Andrew Hartley (Met Office), and Helen Baron (UK Centre for Ecology and Hydrology). The project sits at the interface of Computer Science and Environmental Science , with strong links to Geography , Earth Science , hydrology, drought risk, and climate-related water secur...

Computer Science
Environmental Science
Geography
+5 more

New Today

Publisher
source

University of Michigan

Country flag

United States

Fully funded PhD opportunity at the University of Michigan in the School for Environment and Sustainability (SEAS) with Dr. Lauren E. Gillespie’s research group. The project sits at the intersection of AI , remote sensing , ecology , biodiversity , and environmental science . The lab develops AI-integrated approaches for ecosystem monitoring and works with large-scale environmental data to study environmental change, ecological forecasting, and biodiversity patterns. Research themes mentioned in...

Computer Science
Data Science
Ecology
+8 more

2 days ago

Keywords

Computer Science
Data Science
Machine Learning
Environmental Science
Remote Sensing
Statistical Analysis
Geography
Hydrology
Artificial Intelligence
Computational Physics
Earth Science
Disaster Management
Climate Resilience
Geographic Information System
Social Vulnerability
Statistics
Flood
Statistic

About this position

This PhD project at the University of Bristol addresses the urgent global challenge of flood risk by developing a physics-informed AI framework that leverages high-resolution satellite data from the SWOT mission. Floods are among the most destructive natural hazards, causing extensive human, economic, and infrastructural losses worldwide. Traditional flood models often lack the real-time data and computational efficiency required for accurate, global-scale forecasting. This research aims to bridge the gap between flood hazard observation and real-world risk assessment for vulnerable communities and economies.

The project will integrate SWOT satellite data with other remote sensing products (such as Sentinel-1/2) and static datasets (topography, land use) to derive key hydrological variables like water level, slope, and discharge. The core innovation is a physics-informed AI model that combines deep learning with hydrodynamic principles, ensuring predictions are both data-driven and physically plausible. Socio-economic vulnerability will be assessed by integrating global datasets on population density, economic activity, and infrastructure, using indices to translate flood hazard into quantifiable risk for different communities and sectors. Validation will involve comparisons with official hazard maps, historical flood records, and economic loss data, while sensitivity analyses will explore how socio-economic assumptions affect hotspot identification.

The outcome will be high-resolution risk maps that support equitable disaster management and climate adaptation, empowering decision-makers to identify vulnerability hotspots and prioritize resilient infrastructure. The project is supervised by Dr. Ce Zhang, Prof. Jeff Neal, and Prof.

Peter M. Atkinson in the School of Geographical Sciences. Funding is provided through the FLOOD-CDT studentship, covering stipend, tuition fees, and research support.

Applicants should have a strong background in relevant disciplines and an interest in AI, remote sensing, and data analysis. Applications are open for a September 2026 start, with a deadline of January 8, 2026.

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants should hold or expect to obtain a strong undergraduate or master's degree in a relevant discipline such as geography, environmental science, computer science, hydrology, or a related field. Experience or interest in artificial intelligence, machine learning, remote sensing, GIS, or data analysis is desirable. International applicants are eligible; English language requirements apply as per University of Bristol standards.

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts and confirm requirements with the university.

Professors

Dr. at School of Geographical Sciences

University Name
Country flag

United Kingdom

Research Interests

Medical Imaging

Conservation Biology

Remote Sensing

Synthetic Aperture Radar

Aerial Photography

Prof. at School of Geographical Sciences

University Name
Country flag

United Kingdom

Research Interests

Hydrology

Artificial Intelligence

Social Vulnerability

Computer Science

Earth Science

Prof. at School of Geographical Sciences

University Name
Country flag

United Kingdom

Research Interests

Statistics

Hydrology

Statistical Analysis

Social Vulnerability

Flood