[£20,780 per year plus payment of tuition fees (Home rate) and a Research Training Support Grant of £5,000 over 3.5 years.] The University of Exeter invites applications for a fully funded PhD studentship focused on developing next-generation environmental biosensors by harnessing mussel behaviour and machine learning for coastal water quality monitoring. This interdisciplinary project is based at the Streatham Campus and addresses the urgent need for real-time, deployable solutions to monitor and protect marine ecosystems threatened by pollution, eutrophication, and harmful algal blooms (HABs). Bivalves such as mussels are highly sensitive to changes in water quality, exhibiting distinct valve gape behaviours in response to environmental stressors like oxygen depletion, toxic algae, and pollutants. This project aims to transform these natural responses into actionable environmental intelligence by advancing both sensor engineering and behavioural data interpretation. Building on recent innovations at Exeter, the research will translate a novel discrete gape-sensor unit from laboratory and short-term field studies into a fully integrated, real-world monitoring system. The system will feature automated live analysis, integrating machine learning algorithms to interpret complex mussel behavioural patterns and generate real-time alerts for rapid response to pollution events or HABs. The technical innovation lies in combining robust, low-power hall-sensor hardware with wireless communication and advanced analytical software. The project will train machine learning models to distinguish between normal physiological behaviours (such as diurnal rhythms and feeding) and abnormal, stress-induced patterns. This requires expertise in biosciences to characterise mussel responses under controlled exposures, and engineering to design hardware, firmware, and analytical pipelines capable of autonomous field operation. The societal and industrial impact of this research is significant. Coastal communities and aquaculture industries are vulnerable to HABs and pollution events that can cause mass mortalities, economic loss, and health risks. A low-cost, deployable sensor network based on mussel behaviour could provide real-time environmental intelligence, supporting regulatory agencies, aquaculture managers, and marine spatial planners. As climate change increases the frequency and intensity of HABs, such proactive management tools are increasingly vital. The project is delivered through multidisciplinary collaboration. Dr Robert Ellis (Biosciences) provides expertise in bivalve physiology and aquaculture, ensuring robust experimental validation. Dr Jun Chew (Engineering) leads on sensor design, system integration, and embedded software development. Industrial engagement is provided by Prof Mike Allen and SeaGen, a blue-tech company supporting product development and commercialisation strategies. This supervisory team offers a unique environment bridging fundamental biology, applied engineering, and industrial innovation. Funding covers a stipend of £20,780 per year, full tuition fees (Home rate), and a Research Training Support Grant of £5,000 over 3.5 years. Applicants should have a strong background in biosciences, environmental science, engineering, or computer science, and an interest in machine learning, sensor technology, or aquatic biology. English language requirements apply. For project-specific enquiries, contact Dr Robert Ellis at [email protected]. Apply online by 12 January 2025 via the University of Exeter portal.

A fully-funded PhD opportunity is available at the University of Exeter, focusing on the development of next-generation environmental biosensors by harnessing mussel behaviour and machine learning for coastal water quality monitoring. The project is part of the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Landscape Award and is based in the Biosciences department. The research aims to transform water quality analysis through a fully automated environmental monitoring solution, integrating interdisciplinary approaches from biology, environmental science, and computer science. The successful candidate will join a collaborative supervisory team led by Robert Ellis (Senior Lecturer in Ecophysiology and Sustainable Aquaculture, University of Exeter), Dr Zhou Zhou (Engineering, University of Exeter), and Prof. Mike Allen (SeaGen). The project will involve working with living sensors, specifically mussels, to monitor and analyze water quality using advanced machine learning techniques. This interdisciplinary research is ideal for students interested in environmental biosensors, aquatic biology, sustainable aquaculture, and computational analysis. Applicants should have a strong academic background in biology, environmental science, engineering, or computer science, with experience or interest in biosensors, aquatic biology, machine learning, or water quality monitoring. The position is fully funded for UK students, covering tuition fees and providing a stipend for living expenses. International applicants may need to cover the difference in tuition fees. The application deadline is 12th January 2026, and interested candidates should apply via the University of Exeter application portal, ensuring all supporting documents are prepared and eligibility criteria are met. For more information, visit the University of Exeter funding page or contact the supervisory team. This opportunity offers a unique chance to contribute to innovative research in environmental monitoring and biosensor technology within a leading UK institution.

[£20,780 per year plus payment of tuition fees (Home rate) and a Research Training Support Grant of £5,000 over 3.5 years.] The University of Exeter invites applications for a fully funded PhD studentship focused on developing advanced biosensor technology for coastal water quality monitoring. This multidisciplinary project leverages the natural sensitivity of mussels to environmental stressors, such as pollution, eutrophication, and harmful algal blooms (HABs), to create a real-time monitoring system capable of providing early warnings of ecosystem stress. Mussels exhibit distinct valve gape behaviours in response to changes in water quality, making them powerful bio-sensors for environmental monitoring. The project aims to transform an existing prototype discrete gape-sensor unit into a fully integrated, deployable environmental monitoring solution. Building on recent innovations at Exeter, the research will expand current technology to include automated live analysis, integrating machine learning algorithms to interpret complex behavioural patterns of mussels. This will enable the generation of real-time alerts and warnings, allowing for rapid response to pollution events or the onset of HABs. Technical innovation will combine robust low-power hall-sensor hardware, wireless communication, and sophisticated analytical software. Central to the project is the training of machine learning models to distinguish between normal physiological behaviour (such as diurnal rhythms and feeding responses) and abnormal stress-induced patterns. The research requires interdisciplinary expertise, including biosciences to characterise physiological responses under controlled exposures, and engineering to design hardware, firmware, and analytical pipelines for autonomous field operation. The societal and industrial impact of this system is significant. Coastal communities and aquaculture industries are vulnerable to HABs and pollution events that can cause mass mortalities, economic loss, and human health risks. A low-cost, deployable sensor network based on mussel behaviour could provide real-time environmental intelligence, supporting regulatory agencies, aquaculture managers, and marine spatial planners. As climate change increases the frequency and intensity of HABs, proactive management tools will become increasingly vital. The project will be delivered through multidisciplinary collaboration, offering a unique training environment. The supervisory team includes Dr Robert Ellis (Biosciences), who provides expertise in bivalve physiology and aquaculture; Dr Jun Chew (Engineering), who leads sensor design, system integration, and embedded software development; and Prof Mike Allen, who brings industrial engagement through SeaGen, a blue-tech company supporting product development and market strategies. This team bridges fundamental biology, applied engineering, and industrial innovation. Funding for this studentship includes an annual stipend of £20,780, payment of tuition fees at the Home rate, and a Research Training Support Grant of £5,000 over 3.5 years. The position is based at the Streatham Campus, University of Exeter. Applicants should hold or expect to obtain a first or upper second class UK Honours degree, or equivalent, in a relevant discipline such as biosciences, engineering, computer science, or environmental science. Experience in experimental biology, sensor engineering, or machine learning is desirable. International applicants must meet English language requirements. To apply, visit the University of Exeter funding award page and use the online application portal. For project-specific enquiries, contact Dr Robert Ellis at [email protected]. The application deadline is 12 January 2026.