[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.