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Three Fully Funded PhD Opportunities in Informatics, Hydro-environmental Risk, Flood Risk, and AI-Powered Property Risk Assessment Loughborough University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Three fully funded PhD positions. Fees for 2026-27 are funded for both UK and international students, with full-time study for 3.5 years or part-time for 7 years.

Deadline

Expired

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Country

United Kingdom

University

Loughborough University

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Keywords

Computer Science
Environmental Science
Risk Assessment
Geography
Artificial Intelligence
Civil Engineering
Computer Vision
Architecture
Digital Twin Technology
Disaster Resilience
Climate Resilience
Flood Risk
Informatic

About this position

Three fully funded PhD opportunities are available at Loughborough University through the UNESCO Chair in Informatics and Multi-hazard Risk Reduction (UNESCO-IMRR). These projects sit within informatics, disaster risk reduction, climate adaptation, and resilience-focused engineering research.

1) Digital Twin-enabled Monitoring and Assessment of Hydro-environmental Risks in Heritage Masonry Buildings
Supervisors: Dr Zhiqi Hu, Prof Qiuhua Liang
This PhD develops a digital twin framework to assess rainfall, groundwater fluctuation, moisture-related processes, deformation, deterioration, and vulnerability in heritage masonry buildings. It combines point cloud and image data, building information models, and environmental exposure data to support inspection planning, maintenance prioritisation, and resilience-informed decision-making.

2) Data-driven Optimisation of Hydraulic Model Calibration and Flood Risk Interventions for Enhanced Resilience and Investment Efficiency
Supervisors: Prof Qiuhua Liang, Dr Huili Chen, Dr Huili Fang
This project focuses on hydraulic modelling, flood risk, and optimisation of interventions to improve resilience and investment efficiency. It is aligned with data-driven methods for calibration and decision support in flood risk management.

3) AI-Powered Uncertainty-Aware Adaptive Methods for Property Risk Assessment in Climate Change Adaptation and Disaster Resilience
Supervisors: Prof Baihua Li, Dr Huili Chen
This PhD develops novel AI methods for property risk assessment under climate and disaster-related hazards. It emphasises uncertainty-aware multimodal data fusion, decision-theoretic data acquisition, satellite observations, and computer vision to enable adaptive and dynamically updateable risk assessment.

Funding: All three PhDs are fully funded for UK and international students. The projects are full-time for 3.5 years (or part-time for 7 years).

Eligibility: Applicants should have or expect to shortly graduate with at least a UK 2:1 honours degree or equivalent in a relevant subject. International applicants should meet the English language requirement (IELTS 6.5 overall with 6.0 in each component, or TOEFL if applicable).

Application window: Deadline is 9 June 2026. Applicants must submit a CV, certified transcripts and degree certificates, and a two-page personal statement tailored to the project and i-Risk DFA.

Funding details

Three fully funded PhD positions. Fees for 2026-27 are funded for both UK and international students, with full-time study for 3.5 years or part-time for 7 years.

What's required

Applicants must have or expect to shortly graduate with at least a UK 2:1 honours degree or equivalent international qualification from a high-ranking university in a relevant subject. The post states that EU and international applicants should achieve IELTS 6.5 with at least 6.0 in each competency, or provide a TOEFL certificate if applicable. Candidates must submit a CV, certified academic transcripts and degree certificates, and a two-page personal statement addressing research interests in informatics and disaster risk reduction, motivation, project fit, data analytics experience, problem-solving, goal achievement, and resilience to setbacks.

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