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Qinggang Meng

Professor at Loughborough University

Loughborough University

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United Kingdom

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Research Interests

Artificial Intelligence

40%

Human-robot Interaction

30%

Computer Vision

70%

Consensus Algorithms

40%

Mobile Robotics

30%

Deep Learning

30%

Dynamical Systems

30%

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Positions2

Publisher
source

Qinggang Meng

University Name
.

Loughborough University

PhD Studentship: Embedded AI-Powered Marine Biodiversity Monitoring

[Tax-free stipend of £20,780 per annum (in 2025/26) and tuition fees at the UK rate for 3.5 years; Research Training Support Grant (RTSG) of £8,000; International candidates may receive the difference between UK and International tuition fees.] This PhD studentship at Loughborough University offers an exciting opportunity to advance the field of marine biodiversity monitoring through embedded AI and computer vision technologies. In partnership with CEFAS, a global leader in marine science, the project aims to develop scalable, low-cost edge-AI systems for real-time analysis of marine environments. The research will focus on creating robust algorithms capable of classifying diverse marine species and detecting anthropogenic debris under challenging underwater conditions. Building on the Neural Network Enhanced Marine Observation system—a working prototype featuring a shallow-water, edge-AI-enabled spatial camera—the successful candidate will extend its capabilities using novel deep learning and computer vision methods. The project addresses the limitations of current cloud-based solutions by enabling real-time, embedded analysis, which is crucial for efficient and accurate monitoring of nearshore vegetation, shellfish stocks, and epibenthic biodiversity. Supervision will be provided by Professor Qinggang Meng (primary), Professor Baihua Li, and experts from CEFAS, including Jon Hawes and Peter Kohler. The studentship is partially funded by 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 are eligible, with additional support for tuition fee differences, though UKRI rules limit international awards to 30% of funded studentships. Applicants should hold, or expect to obtain, at least a 2:1 degree (or equivalent) in Computer Science, Engineering, or a related discipline, with strong programming skills. English language requirements must be met as specified by the university. The application process involves completing the CENTA studentship application form, applying online via the university portal, and quoting reference 'CENTA2026-LU07'. The deadline for applications is January 7th, 2026, with interviews for shortlisted candidates expected in early February 2026. This position is ideal for candidates interested in interdisciplinary research at the intersection of AI, computer vision, and marine science, with significant real-world impact on environmental monitoring and conservation.

1 month ago

Publisher
source

Qinggang Meng

University Name
.

Loughborough University

PhD Studentship: Embedded AI-Powered Marine Biodiversity Monitoring

[Tax-free stipend of £20,780 per annum (in 2025/26) and tuition fees at the UK rate for 3.5 years. Research Training Support Grant (RTSG) of £8,000. International candidates may have the difference between UK and International tuition fees covered by the University, subject to UKRI funding rules (no more than 30% of studentships to international candidates).] This PhD studentship at Loughborough University offers an exciting opportunity to advance the field of real-time marine biodiversity monitoring using cutting-edge computer vision and edge-AI technologies. In partnership with CEFAS, a global leader in marine science, the project aims to develop scalable, low-cost embedded vision systems capable of analyzing marine biodiversity and detecting anthropogenic debris in challenging underwater environments. The research will focus on designing robust, real-time edge-AI algorithms for accurate classification of diverse marine species and debris, addressing the limitations of current cloud-based computer vision solutions that require specialized expertise and infrastructure. Building on the Neural Network Enhanced Marine Observation system—a working prototype of a low-cost, shallow-water, edge-AI-enabled spatial camera—the project seeks to extend its capabilities for benthic debris classification and comprehensive biodiversity monitoring. The successful candidate will work closely with a multidisciplinary supervisory team, including Professor Qinggang Meng (primary supervisor), Professor Baihua Li, and experts from CEFAS (Jon Hawes and Peter Kohler). 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 Computer Science, Engineering, or a related field, with strong programming skills, and must meet the university's English language requirements. The application process involves submitting a CENTA studentship application form, CV, and supporting documents via the university's online portal, quoting reference 'CENTA2026-LU07'. The deadline for applications is January 7th, 2026, with interviews expected in early February. This project is ideal for candidates passionate about AI, computer vision, and environmental monitoring, offering the chance to contribute to impactful research in marine science.

1 month ago

Articles18

Collaborators5

Angelo Cangelosi

The University of Manchester

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Jorn Mehnen

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Hongmei He

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Goce Trajcevski

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Thomas Martin McGinnity

Professor of Intelligent Systems (Part-Time)

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