Towards increased confidence and public engagement in targeted AI-based frameworks for biodiversity monitoring

Project summary

This project aims to enhance the reliability of AI approaches for biodiversity monitoring with high site-specific accuracy, ultimately supporting more consistent and transparent BNG assessment and reporting. Starting from large pre-trained AI models trained on global datasets such as iNaturalist, the project will fine-tune these models for specific National Trust sites to improve recognition of local plant and animal species while incorporating calibrated measures of uncertainty to enhance interpretability. The project will further investigate how different modeling choices and evaluation metrics affect downstream ecological metrics, increasing the reliability of AI-based frameworks for BNG assessment. By working towards high accuracy and reliability even on low-quality smartphone images taken by visitors or community groups, the project lays the foundation for the development of future public-facing tools that can empower the general public to directly contribute image data to BNG initiatives and connect them with nature.

Student Profile

A degree or higher qualification in a relevant field with a component of mathematics (such as Physics, Computing Science, AI, Statistics, Mathematical Ecology, or related fields) and prior programming experience is desirable. Further, an interest in deep learning, ecology, and citizen science approaches is expected.

This project is only open to Home applicants.

We are happy to support flexible start dates in the 2026/2027 academic year.

Supervisors

Tiffany Vlaar, Primary Supervisor, University of Glasgow

Phil Stephens, Durham University

Thomas Hodgson, CreditNature

Joel Sellors-Moore, National Trust

Colin Torney, University of Glasgow

How to apply?

For more details on the application process, and to apply via the NETGAIN online application form, please visit the NETGAIN website. The deadline for applications is 12 pm, noon, Friday 26 June 2026.

Funding Notes

All NETGAIN Doctoral Focal Award projects have guaranteed funding for 4 years at the UKRI national rate. In 2025/26, this included a tax-free stipend of £20,780 paid in monthly instalments, tuition fees at the Home rate, extensive research support funding, and support for an external placement of up to 6 months. Part-time study is available at a minimum of 50%, funding will be provided pro rata.

This project is only open to Home applicants.