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

[Funding covers annual stipend, tuition fees (at home-fee level), and Research Training Support Grant. International students eligible for up to 30% of cohort; funding does not cover relocation or living costs.]

The University of Birmingham is offering a fully funded PhD studentship focused on developing a Biodiversity Digital Twin by leveraging environmental DNA (eDNA) and artificial intelligence (AI) for advanced monitoring and prediction of biodiversity loss. This project addresses the urgent global challenge of declining biodiversity, which impacts essential ecosystem services such as climate regulation, food provisioning, clean water, and recreation. In response to new UK environmental regulations, there is a pressing need for innovative tools to assess and predict the effects of industrial and human activities on natural biological diversity.

The successful candidate will develop state-of-the-art AI algorithms, including graph neural networks (GNNs), temporal graph networks (TGNs), and spatiotemporal graph neural networks (STGNNs), to model historical biodiversity data from freshwater lake ecosystems across England. These data will be obtained using sediment core environmental DNA, enabling multi-scale, holistic modelling of biodiversity changes across taxonomic groups over space and time. The project aims to identify the main drivers of biodiversity loss and predict future scenarios under both business-as-usual and restoration plans.

A key outcome will be the creation of a Biodiversity Digital Twin—a dynamic simulation tool that integrates spatiotemporal eDNA and environmental data. This tool will facilitate direct assessment of production processes, land use, and other human activities on biodiversity, supporting science-driven conservation strategies. The student will also develop an intuitive analytical dashboard to make these insights accessible to end-users, accelerating the transition from traditional to technologically enhanced biodiversity conservation.

This studentship is funded through the CENTA3 DLA and the Natural Environment Research Council (NERC). Funding includes an annual stipend, tuition fees at the home-fee level, and a Research Training Support Grant. International students are eligible for up to 30% of the cohort, but funding does not cover relocation or living costs. Applicants must hold at least a 2:1 at UK BSc level or a pass at UK MSc level or equivalent, and international applicants must meet the University of Birmingham’s entry requirements.

References supporting the project include recent publications on anthropogenic impacts on freshwater biodiversity, the Time Machine framework for biodiversity monitoring, and the application of deep learning and digital twin technologies in ecology. For further details and to apply, visit the CENTA studentship page or the University of Birmingham’s postgraduate admissions site.