PhD Studentship: AI-driven biodiversity insight: enhancing underwater ecosystem monitoring through advanced computer vision

AI-driven biodiversity insight: enhancing underwater ecosystem monitoring through advanced computer vision

Second Supervisor (External Lead): Professor Kerry Howell (also at UoP)

Lead Supervisor (DoS): Dr Dena Bazazian

Third Supervisor: Dr Pierre Hélaouët

Fourth Supervisor: Dr David Moffat

Applications are invited for a 3.5 year PhD studentship with Marine Research Plymouth – a collaborative partnership between the University of Plymouth, the Plymouth Marine Laboratory and the Marine Biological Association. The studentship is due to start on 1^st October 2025.

This project is one of three topics available for the studentship. We anticipate supporting one position, which will be allocated to the best combination of candidate and project as they emerge from interviews across the pool of available topics.

Project Description

The health of our oceans is critical to the planet’s overall environmental stability, yet marine biodiversity is under increasing threat from climate change, overfishing, and pollution. Traditional methods of monitoring underwater ecosystems are often limited by the challenges of the marine environment, such as difficult access and poor visibility. There is an urgent need for innovative approaches that can provide accurate, real-time biodiversity data. This project seeks to harness Artificial Intelligence (AI) and advanced computer vision to transform underwater monitoring. Automating species identification and behaviour analysis will improve the quality and efficiency of biodiversity assessments, supporting the conservation and sustainable management of marine resources.

The candidate will engage in groundbreaking research at the crossroads of AI, computer vision, and marine biology, working in state-of-the-art facilities at all three Marine Research Plymouth institutions. The student will develop and refine AI models to detect, classify, and analyse marine species from underwater imagery and video. This work will involve processing data from various sources, including remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), and fixed underwater cameras. The candidate will have opportunities for fieldwork to validate the models on diverse marine environments.

This project offers extensive training in AI, machine learning, and computer vision, with a focus on their application in marine biology. The student will gain proficiency in programming languages like Python and will work with AI frameworks such as TensorFlow or PyTorch. Additionally, the candidate will learn advanced techniques in marine data collection and analysis, providing comprehensive skills set that span both computational and ecological domains. The project also includes opportunities for collaboration with international research teams and attendance at leading conferences in both fields of AI and marine science.

Eligibility

Applicants should have a first or upper second class honours degree in an appropriate subject or a relevant Masters qualification. We are looking for a highly motivated candidate with a background in Marine Biology, Computer Science or a related field. Experience in programming, AI, or marine ecology is desirable. The ideal candidate will be passionate about marine conservation and eager to apply AI technology to address the pressing challenges facing our oceans.

Non-native English speakers must have an IELTS Academic score of 6.5 or above (with no less than 5.5 in any element) or equivalent.

For further information on Funding, please click on the link below: 

• Funding

To apply for this position please click on the Apply button above.

The closing date for applications is 12 noon on Monday 6^th January 2025.

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