Publisher
source

Tom Stanton

4 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

Full funding available

Deadline

December 31, 2026
Country flag

Country

United Kingdom

University

Loughborough University

Social connections

How do I apply for this?

Sign in for free to reveal details, requirements, and source links.

More information can be found here

Keywords

Computer Science
Environmental Science
Remote Sensing
Geography
Image Processing
Computer Vision
Image Analysis
Community Science
Aerial Surveying
Ecosystem Monitoring
Drone Imagery

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 full fee coverage subject to UKRI rules.]

This fully funded PhD studentship at Loughborough University offers an exciting opportunity to advance research in environmental monitoring by optimising aerial image analysis for beach litter characterisation and quantification. The project is embedded within a three-year marine litter monitoring campaign on the Isle of Skye, Scotland, and builds on the university’s extensive research in this area, including the '50 Years of Litter on Skye' initiative. The successful candidate will join an interdisciplinary team integrating environmental science, engineering, and social science methodologies, working closely with community partners across Scotland’s west coast.

The research will focus on evaluating the efficacy and suitability of digital image collection and analysis for characterising beach litter on heavily-littered coastlines. The project will assess various image capture techniques, including the use of drones and mobile phones, and explore the potential of different sensor types such as RGB and multispectral cameras. 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.

Supervision will be provided by Dr Tom Stanton (primary), Prof. Cunjia Liu, Prof. Adrian Spencer, and Dr Nicholas Midgley (Nottingham Trent University), offering a breadth of expertise in environmental science, engineering, and computational methods. The studentship is partially funded by NERC and provides 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 are eligible, with the university covering the difference between UK and international tuition fees for successful applicants, subject to UKRI funding rules.

Applicants should hold or expect to obtain at least a 2:1 degree (or equivalent) in Geography, Environmental Science, Computer Science, Engineering, or a related field, or possess an appropriate Master’s degree. Minimum English language requirements apply. The application process involves completing a CENTA studentship application form (available at https://centa.ac.uk/apply/) and submitting it online via the Loughborough University portal, selecting the 'Department of Geography and Environment' and quoting reference CENTA2026-LU09. The deadline for applications is January 7th, 2026, with interviews expected in early February 2026.

This studentship is ideal for candidates interested in interdisciplinary research at the intersection of environmental science, computer vision, and community engagement, with a strong commitment to addressing marine litter challenges through innovative technological solutions.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

Ask ApplyKite AI

Start chatting
Can you summarize this position?
What qualifications are required for this position?
How should I prepare my application?

Professors