Evaluating the influence of NEOM regreening approaches on terrestrial productivity (Funded PhD Studentship) Ref: 5792

Supervisors

Primary Supervisor 

Dr Andy Cunliffe, Oppenheimer Associate Professor of Geospatial Ecology, University of Exeter

Secondary Supervisor

Professor Chunbo Luo, Professor of Computer Science, University of Exeter

Professor Ted Feldpausch, Professor of Terrestrial Ecology and Global Change, University of Exeter

This funded PhD studentship will investigate how plant productivity varies across dryland landscapes and how it responds to land management under changing environmental conditions.

The Saudi NEOM project is one of the largest ecological restoration projects in the world, with major efforts underway to restore vegetation across large dryland regions. However, natural variation in climate and environment makes it difficult to determine whether restoration actions are actually improving vegetation growth. This project will address that challenge by building on our recently developed Relative Productivity Index (RPI), which compares observed vegetation productivity with the productivity expected under local environmental conditions using satellite data and machine learning (doi.org/10.1016/j.ecolind.2025.113208).

Working closely with NEOM, the PhD will investigate how vegetation productivity varies across space and time, how it responds to land management, and how effective different regreening strategies are. The work will provide evidence to help guide large-scale restoration efforts.

The project has three main objectives:

Objective 1: Extend and enhance the Relative Productivity Index (RPI) framework using AI methods to increase its accuracy, efficiency, and spatial detail. The improved approach will be used to map current vegetation condition and identify areas affected by pressures such as overgrazing across Saudi Arabia.

Objective 2: Evaluate the impacts of NEOM’s passive regreening actions, such as restricting livestock grazing and off-road vehicle use. By accounting for environmental variation and incorporating field monitoring data, the project will assess how quickly vegetation recovers and where further intervention may be needed.

Objective 3: Evaluate NEOM’s active regreening efforts, including planting and irrigation. Satellite observations will be used to compare vegetation change in restoration sites with surrounding landscapes, helping to identify which interventions are most effective.

Developing the RPI framework is a priority within the TESS Lab and offers opportunities to collaborate with related projects. The student will have an opportunity to make an extended visit to Saudi Arabia for place-based learning, model validation, and knowledge exchange with the NEOM team. As the project partner provides funding and support, specific terms apply and will be detailed in the offer letter. The University of Exeter is internationally recognised for research on environmental change and its impacts on ecosystems and society.

The studentship will be awarded on the basis of merit. International applicants are welcome to apply; however, they must explain in their cover letter how they would fund the approximately £70,000 difference between Home and international tuition fees. International students should also note that they are responsible for the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. Fee status rules are complex, and applicants who have moved to or from the UK (or the Republic of Ireland) within the past three years, or who have applied for settled status under the EU Settlement Scheme, should seek advice on their eligibility for Home fees.

Entry requirements

The successful candidate will have a strong analytical background in geospatial ecology or a related field, and an interest in applying quantitative approaches to understand how regreening strategies influence vegetation productivity and ecosystem recovery.

Applicants should hold qualifications equivalent to a First or Upper Second Class UK Honours degree, and have obtained, or be about to obtain a masters degree in geospatial ecology, ecology, computer science, environmental intelligence, geographic information systems, or a related discipline.

Much of the analytical work will be undertaken using the R programming language, enabling collaboration with related projects within the research group. The successful candidate will be supported to present their work at international conferences, contribute to reports for the project funder, and share research findings with both scientific and wider audiences. In line with open science practices, project outputs (including data, models, and publications) will be made openly available where possible.

If English is not your first language you will need to meet the English language requirements and provide proof of proficiency. Click here for more information.

How to apply

Apply now

To apply, please click the ‘Apply Now’ button above. As part of the application process you will be asked to upload the following documents:

·       CV (maximum 3 pages). Please do not include photographs, ethnicity, date of birth, marital status, or religion, as these protected characteristics are not be considered under UK equality legislation). 

·       Letter of application (maximum 2 pages) outlining your academic interests, prior research experience, and motivation to undertake this specific project.

·       Academic Transcripts showing subjects studied and grades/marks obtained (an interim transcript is acceptable if you are still studying).

·       Two academic references from referees familiar with your academic work. Referees may alternatively email references direct to PGRApplicants@exeter.ac.uk quoting the studentship reference number.

If you are not a national of a majority English-speaking country you will need to submit evidence of your proficiency in English.

The closing date for applications is midnight on the 13^th of April 2026. 

Interviews will be held in early May.

All application documents must be submitted in English. Certified translated copies of academic qualifications must also be provided.

Please quote reference 5792 on your application and in any correspondence about this studentship.

Summary