Publisher
source

Newcastle University

PhD Studentship: Real-Time River Water Quality Forecasting through Integrated Hydrodynamic and Surrogate Modelling Newcastle University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Jan 30, 2027

Country flag

Country

United Kingdom

University

Newcastle University

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Keywords

Computer Science
Machine Learning
Environmental Science
Hydrology
Civil Engineering
Earth Science
Uncertainty Analysis
Sensitivity Analysis
Ecological Modeling
Surrogate Modeling
Evolutionary Algorithm

About this position

[£25,726 tax-free annual living allowance, research training support grant of £20,000, and 100% fees paid. Funded by EPSRC and Reece Foundation.]

This fully funded PhD studentship at Newcastle University offers an exciting opportunity to advance real-time river water quality forecasting by integrating hydrodynamic and surrogate modelling approaches. The project addresses the urgent challenge of predicting water quality following contamination events, such as those caused by Combined Sewer Overflows (CSOs), which pose significant risks to public health, ecosystems, and urban water environments. These risks are exacerbated by climate change, urbanisation, and ageing infrastructure.

The research will develop a computationally efficient framework that combines high-fidelity physics-based hydrodynamic models with data-driven surrogate models. The initial phase involves constructing a multi-layer hydrodynamic model to capture key three-dimensional flow processes in riverine and estuarine systems. This model will be coupled with advection–diffusion–reaction equations to simulate pollutant transport, mixing, and biochemical processes. To enable rapid, real-time predictions, a machine-learning surrogate model based on Gaussian process regression will be developed and trained using datasets generated by the numerical solver. This surrogate will emulate critical hydrodynamic and water quality responses, providing robust uncertainty quantification to support reliable decision-making in emergency scenarios.

Evolutionary algorithms will be used to efficiently explore the parameter space and conduct sensitivity analyses. The integrated modelling framework will be validated through analytical test cases, laboratory experiments, and field measurements. A real-world case study on the Ouseburn in Newcastle upon Tyne will demonstrate the framework’s capability for real-time water quality forecasting and its potential to inform decisions that protect river users from health risks.

This studentship is part of the Water Infrastructure & Resilience (WIRe) Centre for Doctoral Training (CDT), funded by EPSRC and the Reece Foundation. The award includes a tax-free annual living allowance of £25,726, a research training support grant of £20,000, and full payment of tuition fees. The programme is open to both home and international applicants, including those from the EU, who meet the eligibility criteria. Applicants should hold an MEng/MSc in a relevant subject or a first or upper second class undergraduate degree (2:1), and demonstrate enthusiasm for research, independent working ability, strong analytical skills, and excellent communication skills. Non-native English speakers require an IELTS score of 6.5 overall (minimum 5.5 in all sub-skills), and international applicants may need an ATAS certificate.

The studentship will commence on 28th September 2026 and will run for four years. For application, candidates must use the Newcastle University Apply Portal, select the programme code 8209F, and provide the studentship code WRII2604 in their application. No separate research proposal is required. For further information, contact [email protected].

Funding details

Available

What's required

Applicants must have an MEng/MSc in a relevant subject or a first or upper second class undergraduate degree (2:1). Essential requirements include enthusiasm for research, ability to work independently, excellent analytical skills, and strong verbal and written communication skills. Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills. International applicants may require an ATAS clearance certificate prior to obtaining their visa.

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