[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.