AI-INTERVENE are now open for applications to join the first cohort of PhD students to start in October 2026.
AI-INTERVENE is committed to making support for applicants accessible to everyone.
We welcome and encourage applications from people of all backgrounds and are committed to making our application process accessible to everyone. This includes making reasonable adjustments, for people who have a disability or a long-term condition and face barriers applying to us. AI-INTERVENE offers interview guidance to underprivileged groups, so we encourage all to apply. You can contact us at any time to ask for guidance.
For 2026 entry (2nd annual cohort) we will be recruiting up to 12 students.
Note: All students (both home and international) students are eligible to apply with the following conditions. For home students full funding will be provided by AI-INTERVENE. For international students applying to PhD projects where UCL are the degree awarding body (see individual advert on FindAPhD.com) full funding will be provided. For international students applying to PhD projects where the University of Reading are the degree awarding body (see individual advert on FindAPhD.com) UKRI funding only covers home fees which increase annually, therefore international students will be required to pay the difference between the International and Home student fees (currently ~£16000-£19000/year).
Applying data science and AI methods to biodiversity data is a truly interdiscipinary challenge. We welcome applicants from a diverse range of backgrounds and experience. For example, you may have a computer science, engineering or mathematics background, or equally, an ecology, biology or environmental science background. All are welcome.
Please see the details of specific projects (see link below).
How to Apply?
To apply for an AI-INTERVENE PhD please visit FindaPhd’s Ai-INTERVENE landing page at: https://www.findaphd.com/phds/ai-intervene-dfa This page contains full details on the list of open projects. Once you have selected a project please apply directly via the Good Grants platform using the following dedicated link: ai-intervene-dfa.grantplatform.com
The deadline for applications is January 19th 2026.
The list of projects for 2026 entry are as follows. All PhD degrees wil be conferred through either the University of Reading (UoR) or University College London (UCL).
| Project ID | Project Title | Lead Supervisor | Host Institution |
| 02 | AI-Driven Biodiversity Monitoring in Kelp Forests : Estimating Shark Populations through Machine Learning | Glyn Barrett | UoR |
| 03 | Learning from Nature: Cognitive Navigation of Legged Robots for Biodiversity Monitoring | Dimitrios Kanoulas | UCL |
| 04 | AI-enabled Construction of an Ecosystem Management Framework that Supports UK Seabirds Conservation | Nathalie Pettorelli | ZSL |
| 05 | Autonomous Multi-Agent Systems for Warehousing Worldwide Biodiversity Data | Ferran Espuny-Pujol | UoR |
| 07 | How and Why is the Timing of Egg Laying Changing in UK Wild Birds? | Ken Norris | NHM |
| 08 | Improving Methodologies of Whole Genome Assembly and Phylogeny Building in Historical Fungal Collections | Ester Gaya | RBG Kew |
| 09 | Medicinal Plants Entering Trade: Local Use to Global Impact | Julie Hawkins | UoR |
| 10 | Restored Saltmarsh Trajectories (Restored SMART) – A Machine Learning Evaluation of In Situ Saltmarsh Restoration Methods | Jonathan Dale | UoR |
| 11 | Automating Descriptions for the World Flora Online | Alastair Culham | UoR |
| 12 | Peatland Pulse: A Smart Sensing Approach to Uncover Biodiversity–Carbon Links during Peatland Restoration | Jenna Lawson | UKCEH |
| 14 | CV-Pollin: Low-Energy Computer Vision for Plant-Pollinator Network Monitoring | Deepa Senapathi | UoR |
| 15 | Privacy-Preserving Distributed Embedded AI for Biodiversity Monitoring | Xiaomin Chen | UoR |
| 17 | The Colourful Spectrum of Orchid Evolution | Chris Vendetti | UoR |
| 18 | Adapting to a Changing World: The Mechanisms of Genetic Adaptation to Habitat Aridification | Aida Andres | UCL |
| 19 | Unlocking Palaeo-Historical Biodiversity Data to Inform Ecological Baselines through AI | Stephen Pates | UCL |
| 20 | Decoding Airborne eDNA through AI to Uncover Biodiversity and Environmental Health Patterns | Susheel Bhanu Busi | UKCEH |
| 21 | Bayesian and Machine Learning Approaches to Reveal the Evolutionary Synamics of the Early Diversification, Dispersal, and Adaptive Evolution of Living and Fossil Felidae | Manabu Sakamoto | UoR |
| 22 | Developing AI for the Global Monitoring of Big Cats: Cheetah as a Case Study | Sarah Durant | ZSL |
| 23 | Characterisation of the Biodiversity and Ecology of Bacteriophages using Large-Scale Analyses of Metagenomic Data | Francois Balloux | UCL |
| 24 |
Assessing the Value Added by AI in Seasonal Drought Forecasting for Desert Elephant Conservation |
Guy Cowlishaw | ZSL |
| 25 |
Smart Wasps: A Technological Approach to Unravelling The Secrets of an Insect Apex Predator |
Seirian Sumner | UCL |
| 26 |
FlightPath: Predicting Avian Influenza Evolution through AI-Powered Phylodynamics and Bird Migration Modelling |
Lucy van Dorp | UCL |
| 27 |
Integrating AI and Aerial Imagery for Automated Wildlife Monitoring in Savannah Ecosystems |
Rajan Amin | ZSL |
| 28 |
AI-Integrated Network Ecosystem Models for Predicting Biodiversity Change |
Kate Jones | UCL |
| 29 | Expanding Biodiversity Change Horizons with Predictive Models and Large Language Models | Robin Freeman | ZSL |
What Happens Next?
After the application deadline ( January 19th 2026) the AI-INTERVENE Training and Selection Committee will idenity candidates who meet the PhD entry requirements. During February 2026 candidates will be invited to an interview with the supervisory team for the project applied for. Interviews will be online and will be scheduled up until the end of February 2026. Candidates will be expected to demonstrate motivation for joining the AI-INTERVENE programme. Shortlisting and interviews will be managed by the project supervisory team, reporting to the AI-INTERVENE Training and Selection Committee. The AI-INTERVENE Training and Selection Committee will then make the final selection of candidates. Offers will be sent to candidates in early March 2026 with the final decision expected within 2 weeks. Successful candidates will then have the opportunity to meet meet with their supervisory team. It is anticpated that final offers to applicants will be made during March 2026.