AI-INTERVENE is now closed for applications to join the first cohort of PhD students to start in September 2025.
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 2025 entry (1st annual cohort) we will be recruiting up to 12 students.
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.
Note: AI-INTERVENE can support up to 25% international students. Addiitonally, international students cannot be hosted by non-HEI institutions due to visa regulations.
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 27th 2025.
The list of projects for 2025 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 |
| 06 | ReefNet: Expert-informed Benchmarks and Machine Learning Systems for Coral Reef 2D /3D Visual Understanding | Xiang Li | UoR |
| 08 | WildFusion: Sustainable Wildlife Health Monitoring through Multi-Sensor Fusion | Amir Patel | UCL |
| 09 | Quantifying Species Distributions and Changes in a Global Biodiversity Hotspot using Museum Specimens and AI | Deepa Senapathi | UoR |
| 14 | Advancing Volunteer-Led Biodiversity Monitoring with Generative AI and Data Science | Tom August | UKCEH |
| 15 | Leveraging AI and Machine Learning to Investigate Shy Shark (Haploblepharus spp.) Abundance in Kelp Forests | Glyn Barrett | UoR |
| 17 | Deep Learning in Remotely Sensed Image Understanding for Biodiversity and Ecosystem Services | Hong Wei | UoR |
| 18 | Leveraging Machine Learning and Shotgun Metagenomics to Address Antibiotic Resistance in Environmental Microbiomes | Soon Gweon | UoR |
| 19 | Leveraging Artificial Intelligence for Real-Time Early-Warnings of Human-Wildlife Conflict | Vicky Boult | UoR |
| 23 | Building a Framework to Aid the Identification and Management of Key Ecosystems for UK Seabirds | Nathalie Pettorelli | IoZ |
| 27 | Sounds of the Forest: Examining Patterns in Woodland Biodiversity using AI and Machine Learning | Brian Pickles | UoR |
| 32 | Spore It Out: Giving Fungal Spores a Voice | Vasco Fachada | RBG Kew |
| 34 | Retrodeformation and Phenomic Data Capture from Fossils to Reconstruct Response to Past Mass Extinction and Global Climate Change | Anjali Goswami | NhM |
| 35 | Communicating Biodiversity Change through LLMs: Can AI Turn ‘Hard’ Data ‘Soft’ to Motivate Pro-Environmental Behaviour? | Tom Oliver | UoR |
| 36 | AI4Plants: Unlocking Plant Biodiversity Insights with AI and Computer Vision | Muhammad Shahzad | UoR |
| 40 | Protecting Wildlife in Sub-Saharan African with Imaging Drones and Human-in-the-Loop AI Systems | Benjamin Kellenberger | UCL |
| 41 | Turn the Page: New Methods to Mobilise Data for Monographers | Nicky Nicolson | RBG Kew |
| 44 | A Characterisation of the Biological Features of Phages through Large-Scale Analyses | Francois Balloux | UCL |
| 47 | How Does Ecological Persistence Depend on Rapid Evolutionary Responses? Using Deep Learning to Understand How Genomic Variation Determines Climate Eesponses in UK Butterflies. | Jon Bridle | UCL |
| 49 | Using Neural Networks to Improve our Understanding of Species Distributions | Kiran Dhanjal-Adams | RBG Kew |
| 50 | Computer Vision Depth Models of Wildlife Imagery for Conservation Monitoring | Marcus Rowcliffe | IoZ |
| 53 | River Rhythm: A Sonic Approach to Monitoring Real-Time River Health | Steven Gray | UCL |
| 55 | MM-BioGraph: Multimodal Data Analysis for Link Prediction in Biodiversity Graphs | Alan Guedes | UoR |
| 57 | Tree Species Diversity Mapping through Proximal Sensing and Multi-view Convolutional Neural Networks | Martin Mokros | UCL |
| 58 | Expanding Biodiversity Change Horizons with Predictive Models and Large Language Models | Robin Freeman | IoZ |
| 59 | Quantify Global Patterns and Drivers of Forest Resilience using Graph Neural Networks | Daniel Maynard | UCL |
| 60 | Next-Generation Biodiversity Assessments through Remote Sensing and Deep Learning | Alexandre Antonelli | RBG Kew |
What Happens Next?
After the application deadline ( January 27th 2025) the AI-INTERVENE Training and Selection Committee will idenity candidates who meet the PhD entry requirements. During February 2025 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 2025. 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 2025 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 2025.