整合浮游生物成像技术探索生态系统结构与功能博士研究员（ARIES奖学金）

Funding for: UK Students, EU Students, International Students

Funding amount: Fully-funded ARIES studentship covering Home fees, maintenance stipend (£21,805 p.a. for 2026-27) and a research training and support grant (£2,500). Limited number of studentships available for international applicants, with the difference between ‘Home’ and ‘International’ fees being waived by the registering university. ARIES funding does not cover additional costs associated with relocation to, and living in, the UK.

Hours: Full-Time or Part-Time

Closes: 16 December 2026

Background

Marine plankton communities are sensitive indicators of environmental change and play a vital role in ocean food webs, fisheries productivity and carbon cycling. Understanding how these communities are structured, and the factors that influence their organisation, is essential for predicting future ecosystem change and the efficiency of the biological carbon pump. As imaging technologies become increasingly accessible alongside traditional net sampling, new opportunities are emerging to study plankton community structure using size-based approaches that provide insights into trophic dynamics, food web interactions and carbon export processes.

This project will use size-based imaging technologies of marine plankton communities to improve understanding of ecosystem function, inform ecosystem-based management, and support global efforts to monitor ocean health and climate change impacts.

The project

You will combine traditional net-derived plankton data with image-based observations from ship surveys and oceanic moorings to investigate seasonal and interannual changes in plankton community structure in the Scotia Sea (Southern Ocean) and Western English Channel. You will explore how environmental drivers such as temperature, nutrient availability, sea ice, and mixed layer depth influence community size spectra, vertical particle flux and carbon export. This will be supported by sediment trap data and elemental analysis. A key aim is to assess how effectively imaging techniques complement traditional net sampling for characterising plankton communities.

You will gain skills in plankton taxonomy, image processing, ecological statistics, safe laboratory practices, oceanographic data handling, and field ecology. Laboratory work will include sample processing, microscopy, and benchtop imaging. Depending on your interests, the project could also explore linking plankton size patterns to krill dynamics, carbon export or nutritional quality, or developing tools for rapid ecosystem monitoring using machine-learning approaches. Participation in UK-based fieldwork will be available, offering training in quantitative plankton sampling and seagoing skills. Participation in Antarctic fieldwork may be a possibility but cannot be guaranteed.

For queries about the studentship, please contact the Supervisor, Mrs Elaine Fileman, at ese@pml.ac.uk .

Person specification

We seek an inquisitive and motivated candidate with a background in marine science, biological oceanography, environmental science, data science, computer science or related discipline. Strong analytical, numerical and practical skills are essential. Experience in coding or applying quantitative methods in a biological or ecological discipline is desirable, but full training will be provided.

Acceptable first degree subject(s): Marine Science/ Environmental Science/ Natural Sciences or equivalent £21,805 p.a