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Tom Stanton

11 months ago

PhD Studentship: Optimising Aerial Image Analysis for Beach Litter Characterisation and Quantification Loughborough University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

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Country

United Kingdom

University

Loughborough University

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Keywords

Computer Science
Environmental Science
Geography
Image Processing
Computer Vision
Quantitative Analysis
Drone Technology
Citizen Science
Hyperspectral Imaging
Aerial Surveying
Coastal Ecology
Marine Pollution
Digital Methods

About this position

[Fully funded studentship, partially funded by NERC, includes a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant (RTSG) of £8,000. International candidates may be eligible for fee support to cover the difference between UK and International tuition fees, subject to UKRI rules (max 30% international studentships).] This fully funded PhD studentship at Loughborough University focuses on optimising aerial image analysis for the characterisation and quantification of beach litter, building on the university’s extensive research into marine litter on the Isle of Skye and Scotland’s west coast. The project is part of a three-year marine litter monitoring campaign and involves close collaboration with community partners.

The research will evaluate the effectiveness of digital image collection and analysis methods, including the use of drones and mobile phones, to monitor heavily-littered coastlines. It will assess various image capture techniques and sensor types (such as RGB and multispectral) to generate high-quality beach litter images. The analysis will compare manual digital approaches (e.g., Dot Dot Goose) with the development of automated computer vision algorithms for marine litter characterisation and quantification. The interdisciplinary nature of the project requires integrating environmental science, engineering, and community science methodologies.

The successful candidate will join a team of researchers and work with community groups to advance practical solutions for marine litter monitoring. Funding is provided through NERC and includes a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant of £8,000. International candidates may be eligible for additional fee support, subject to UKRI rules.

Applicants should have at least a 2:1 degree (or equivalent) in Geography, Environmental Science, Computer Science, Engineering, or a related field, and meet minimum English language requirements. Applications require a CENTA studentship application form, CV, and supporting documents, with a deadline of January 7th, 2026. Interviews for shortlisted candidates will be held in early February 2026.

Funding details

Available

What's required

Applicants must hold, or expect to gain, at least a 2:1 degree (or equivalent) in a relevant subject such as Geography, Environmental Science, Computer Science, Engineering, or an appropriate Master’s degree. Minimum English language requirements must be met. International candidates should check eligibility and funding rules. A CV and CENTA studentship application form are required for application.

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Professors

Dr. at Loughborough University

University Name
Country flag

United Kingdom

Research Interests

Artificial Intelligence

Marine Biology

Computer Science

Citizen Science

Aerial Surveying

Prof. at Loughborough University

University Name
Country flag

United Kingdom

Research Interests

Human-robot Interaction

Artificial Intelligence

Autonomous Navigation

Environmental Science

Computer Science

Prof. at Loughborough University

University Name
Country flag

United Kingdom

Research Interests

Artificial Intelligence

Marine Biology

Geography

Environmental Science

Image Processing

Dr. at Loughborough University

University Name
Country flag

United Kingdom

Research Interests

Marine Biology

Artificial Intelligence

Citizen Science

Computer Science

Aerial Surveying