Publisher
source

Kingston University

Building Flexibility into Long-Term Water Resources System Planning and Management Strategies Kingston University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD Project (Students Worldwide)

Deadline

Expired

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Country

United Kingdom

University

Kingston University

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Keywords

Computer Science
Data Science
Environmental Science
Mathematics
Decision Making
Civil Engineering
Python Programming
Adaptation
Resiliency
Climate Resilience

About this position

This PhD project at Kingston University focuses on developing flexible and adaptive strategies for long-term water resources system planning and management. Sustainable water resource policies must account for future changes driven by geomorphologic processes, aging infrastructure, shifting demand, and variable water supplies. The project addresses the challenge of 'deep' uncertainty, where predictions about future conditions are highly unreliable, and emphasizes the need for decision makers to avoid irreversible actions and to adapt policies as new information emerges.

Water sector infrastructure is capital-intensive and requires significant long-term investments. Without flexibility in planning and design, infrastructure may need costly retrofitting or replacement before its intended lifespan, exposing society to higher risks and suboptimal adaptation decisions. This research aims to develop a capacity expansion optimization model that enables water planners to schedule infrastructure upgrades and investments using adaptive strategies, building on recent advancements in the field.

The initiative is particularly timely, as countries like the UK are planning major infrastructure investments to ensure water security over the next decade. National guidelines and government policies increasingly stress the importance of integrating flexibility into water resource system designs. The project will leverage current literature and methodologies to inform robust, adaptive planning approaches.

Applicants should have a strong background in civil or environmental engineering, mathematics, or computer science, with skills in mathematical optimization, data science for large datasets, and Python programming. The project is co-supervised by Dr S Padula and Professor Jean-Christophe Nebel, who brings extensive expertise in AI, pattern recognition, and game theory, as well as strong industry and community connections through his role as Director of Kingston University's Knowledge Exchange & Research Institute for Cyber, Engineering & Digital Technologies.

Funding is available through Kingston University's Graduate School studentships competition for October 2026 entry. Interested candidates should consult the PhD Studentships and Faculty of Engineering, Computing and the Environment research webpages for application details. The application deadline is March 4, 2026.

References supporting the project include key works on adaptive governance, risk-based water security management, climate change adaptation, and robust decision-making under uncertainty. For further information and to apply, visit the provided links.

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants should have a strong background in civil or environmental engineering, mathematics, or computer science. Ideal candidates will demonstrate proficiency in mathematical optimization, data science for large datasets, and Python programming. No specific GPA or language test requirements are mentioned, but a solid academic record and relevant technical skills are expected.

How to apply

Review the Graduate School Studentships information at Kingston University London and the Faculty of Engineering, Computing and the Environment research webpage. Prepare your application according to the guidelines provided on these pages. Submit your application before the stated deadline.

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