professor profile picture

Nicholas Midgley

Dr. at Loughborough University

Loughborough University

Country flag

United Kingdom

This profile is automatically generated from trusted academic sources.

Google Scholar

.

ORCID

.

LinkedIn

Social connections

How do Turkish students reach out?

Sign in for free to see their profile details and contact information.

Meet Kite AI

Contact this professor

LinkedIn
ORCID
Google Scholar

Research Interests

Marine Biology

10%

Artificial Intelligence

10%

Aerial Surveying

20%

Quantitative Analysis

20%

Citizen Science

20%

Geography

20%

Drone Technology

20%

Ask ApplyKite AI

Start chatting
How can you help me contact this professor?
What are this professor's research interests?
How should I write an email to this professor?

Positions2

Publisher
source

Tom Stanton

University Name
.

Loughborough University

Optimising Aerial Image Analysis for Beach Litter Characterisation and Quantification (Ref: CENTA2026-LU09)

This PhD project at Loughborough University aims to optimise aerial image analysis for the characterisation and quantification of beach litter, building on the university’s extensive research into marine litter, including the '50 Years of Litter on Skye' initiative. The research responds to a three-year marine litter monitoring campaign on the Isle of Skye and involves collaboration with community partners across Scotland’s west coast. The project is highly interdisciplinary, integrating environmental science, engineering, and community science methodologies. The successful candidate will evaluate the efficacy and suitability of digital image collection and analysis for beach litter characterisation, focusing on heavily-littered coastlines. The research will assess the practicality of 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 sensors. Image analysis will involve both manual digital approaches (e.g., Dot Dot Goose) and the development of automated computer vision algorithms for marine litter characterisation and quantification. The project is designed to enhance marine litter monitoring methods and support community-led environmental initiatives. 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 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 have at least a 2:1 degree (or equivalent) in a relevant field such as Geography, Environmental Science, Computer Science, or Engineering, and must meet the university’s English language requirements. The position is available full-time (3.5 years) or part-time (7 years), with a start date in October 2026. Applications close on January 7th, 2026, and interviews for shortlisted candidates will be held in February 2026. For application instructions, candidates should complete the CENTA studentship application form and apply online, quoting the reference number CENTA2026-LU09.

1 month ago

Publisher
source

Tom Stanton

University Name
.

Loughborough University

PhD Studentship: Optimising Aerial Image Analysis for Beach Litter Characterisation and Quantification

[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.

1 month ago