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Nanzhe Wang

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Fully Funded PhD Studentship in Machine Learning for Groundwater Pollution at Heriot-Watt University Heriot-Watt University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Competitive, fully funded PhD studentship available through IAPETUS for 3.5 years, covering tuition fees at the UK Home rate, a stipend, and research and training support. International fee arrangements are subject to host university policy.

Deadline

Jan 5, 2027

Country flag

Country

United Kingdom

University

Heriot-Watt University

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Keywords

Computer Science
Geology
Environmental Science
Hydrogeology
Earth Science
Uncertainty Analysis
Data Assimilation
Reinforcement Learning
Water Pollution
Geothermal Engineering
Statistics
Bayesian Inversion
Physics
ML

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About this position

PhD Studentship Opportunity: Machine Learning for Groundwater Pollution at Heriot-Watt University, Edinburgh, UK.

This fully funded PhD is offered through the Iapetus DTP NERC Doctoral Training Partnership (DTP) Studentship Competition 2026–27. The project title is Reconstructing Groundwater Pollution Release Histories under Geological Uncertainty Using Machine Learning and Adaptive Monitoring.

The research combines several high-impact areas: groundwater flow and contaminant transport modelling, machine learning and AI surrogate modelling, Bayesian inversion, data assimilation, uncertainty quantification, reinforcement learning, and adaptive monitoring design. It is well suited to students interested in environmental science, hydrogeology, geoscience, geoenergy, computational modelling, applied mathematics, and AI for subsurface systems.

Host and supervision: The host institution is Heriot-Watt University in Edinburgh, UK. The supervisory team includes Dr Nanzhe Wang (Heriot-Watt University), Dr Marco Bianchi (British Geological Survey), and Dr Yihuai Zhang (University of Glasgow).

Funding: The studentship is competitive and fully funded for 3.5 years, covering tuition fees at the UK Home rate, a stipend, and research and training support. International fee arrangements depend on host university policy.

Eligibility: Applicants with backgrounds in hydrogeology, geoscience, geoenergy, environmental science, computational modelling, machine learning, applied mathematics, or related disciplines are welcome. The opportunity is aimed at PhD candidates. Home and sponsored international applicants may apply; international applicants must contact the supervisor in advance, and each supervisory team can shortlist a maximum of one international applicant.

Application window: Applications open on 6 November 2026. The deadline for Home and sponsored international applicants is 5 January 2027 at 12:00 noon GMT. International applicants must email [email protected] by Monday, 7 December 2026.

How to apply: Read the project page via the application link, check eligibility, and submit your application within the stated window. International applicants should first contact Dr Nanzhe Wang by email before applying.

Funding details

Competitive, fully funded PhD studentship available through IAPETUS for 3.5 years, covering tuition fees at the UK Home rate, a stipend, and research and training support. International fee arrangements are subject to host university policy.

What's required

Applicants with backgrounds in hydrogeology, geoscience, geoenergy, environmental science, computational modelling, machine learning, applied mathematics, or related disciplines are encouraged to apply. The post indicates Home and sponsored international applicants may apply, with international applicants required to contact the supervisor by 7 December 2026 and each supervisory team able to shortlist a maximum of one international applicant.

How to apply

Review the project details and application information at the provided link. Applications open on 6 November 2026. Home and sponsored international applicants must apply by 5 January 2027 at 12:00 noon GMT. International applicants must email Nanzhe Wang by Monday, 7 December 2026 before applying.

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Professors

Assistant Professor

University Name
Country flag

United Kingdom

Research Interests

Statistics

Hydrogeology

Earth Science

Environmental Science

Uncertainty Analysis