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Abigail McQuatters-Gollop

9 months ago

PhD Studentship - Marine Sciences: Understanding Plankton Biodiversity and Ecosystem Change by Applying Machine Learning (CASE Studentship, SERVO) University of Plymouth in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

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Country

United Kingdom

University

University of Plymouth

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Keywords

Computer Science
Data Science
Machine Learning
Environmental Science
Biology
Marine Biology
Earth Science
Image Classification
Image Sensor

About this position

[Full Home or International tuition fees plus a stipend at the UKRI rate (£20,780 per annum for 2025/26; 2026/27 rate to be confirmed). Last 6 months of the four-year registration period is self-funded for writing-up.]

The University of Plymouth invites applications for a 3.5-year PhD studentship in Marine Sciences, focusing on understanding plankton biodiversity and ecosystem change through the application of machine learning. Hosted by the Marine Institute, this CASE studentship (SERVO) offers the opportunity to join the UK's largest concentration of marine researchers and a vibrant community of PhD students. The project addresses critical gaps in plankton monitoring and biodiversity assessment by leveraging recent advances in imaging technologies and machine learning classifiers. Plankton are essential to marine food webs and global carbon cycles, serving as sensitive indicators of environmental change and climate impacts on ocean biodiversity. However, current monitoring methods are insufficient for detecting biodiversity shifts and informing conservation policies.

This studentship will apply existing biodiversity policy indicators to new plankton image data, expanding datasets and improving assessments under the UK Marine Strategy and OSPAR frameworks. The candidate will collect plankton images using an innovative benchtop flow-through imaging sensor and integrate these with existing datasets. Field work opportunities include collaboration with Cefas and instrument testing at the University of British Columbia. A novel machine learning image classifier will be used to identify plankton taxa and quantify ecological traits such as size and biovolume, which are crucial for biodiversity analyses and policy evaluation but often missing from traditional data.

The research will characterise spatio-temporal ecological changes in plankton communities in the Northeast Atlantic. The successful candidate will gain expertise in machine learning, plankton taxonomy, ecological trait analysis, and biodiversity indicator development, contributing to the UK and OSPAR Pelagic Habitats Expert Groups. Professional development is supported through the Plankton and Policy Research Unit and the Marine Research Plymouth early career network.

Eligibility requires a first or upper second class honours degree or a Masters in ecology, marine biology, data science, environmental sciences, or related fields. Interdisciplinary candidates with strong quantitative skills are encouraged to apply. The studentship covers full Home or International tuition fees and a stipend at the UKRI rate (£20,780 per annum for 2025/26; 2026/27 rate to be confirmed). The final six months of the four-year registration period are self-funded for writing-up. The application deadline is 2 February 2026. For informal enquiries, contact Professor Abigail McQuatters-Gollop. Apply via the University of Plymouth studentships page.

Funding details

Available

What's required

Applicants must have a first or upper second class honours degree or a Masters qualification in ecology, marine biology, data science, environmental sciences, or related fields. Interdisciplinary backgrounds and strong quantitative skills are particularly encouraged. No specific language test requirements are mentioned.

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Professors

Professor at University of Plymouth

University Name
Country flag

United Kingdom

Research Interests

Marine Biology

Oceanography

Environmental Science

Biology

Computer Science

Professor at University of Plymouth

University Name
Country flag

United Kingdom

Research Interests

Marine Biology

Ecology

Environmental Science

Biology

Data Science