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University of Birmingham

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PhD Studentship: Biodiversity Digital Twin: Leveraging Environmental DNA and Artificial Intelligence for Monitoring Biodiversity Loss University of Birmingham in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Jan 6, 2027

Country flag

Country

United Kingdom

University

University of Birmingham

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Keywords

Computer Science
Environmental Science
Biology
Conservation Biology
Artificial Intelligence
Earth Science
Digital Twin Technology
Freshwater Ecology
Ecological Modeling
Statistics
Environmental Dna
Bioinformatic

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About this position

[Funded through the CENTA3 DLA by the Natural Environment Research Council (NERC). Funding covers an annual stipend, tuition fees at home-fee level, and a Research Training Support Grant. International students are eligible up to 30% of the cohort, but additional moving/residing costs in the UK are not covered.]

This PhD studentship sits within a biodiversity-focused project that aims to build a digital twin for freshwater lake ecosystems, using environmental data and sediment-core environmental DNA to better understand and predict biodiversity loss.

The project combines ecology with advanced computational approaches. The successful doctoral researcher will develop artificial intelligence methods—including graph neural networks, temporal graph networks, and spatiotemporal graph neural networks—to analyse historical biodiversity data collected from freshwater lakes across England. These models will integrate spatiotemporal eDNA and environmental information to simulate how biodiversity changes over space and time, and to identify the main drivers behind those changes.

A further component of the project is the creation of an intuitive analytical dashboard so that the resulting tool can be used by end users to assess the biodiversity impacts of production processes, land use, and other human activities. The work is intended to support more science-driven approaches to biodiversity conservation by combining computational modelling, bioinformatics, and applied environmental insight.

The studentship is offered through the CENTA3 doctoral training environment and is associated with the University of Birmingham. The project emphasises multi-scale, community-level biodiversity analysis rather than species-by-species approaches, and is grounded in current challenges around conserving ecosystem services and understanding biodiversity decline.

Funding details

Available

What's required

Applicants should have at least a 2:1 at UK BSc level or a pass at UK MSc level, or an equivalent qualification. International applicants must meet the University of Birmingham’s international student entry requirements, including English language requirements. International students are eligible for studentships up to 30% of the cohort.

How to apply

Click the Apply button on the advert to start the application. For general CENTA studentship guidance, consult the CENTA apply page.

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