PhD Studentship in Environmental Intelligence: AI for Biodiversity and Conservation
University of Exeter
Exeter, United Kingdom
General Description
The University of Exeter is offering a fully funded PhD studentship in Environmental Intelligence, focusing on the application of artificial intelligence to biodiversity and conservation challenges. This interdisciplinary research opportunity is part of Exeter’s Environmental Intelligence initiative, which integrates data science, ecology, and environmental research to address critical global issues.
The project will involve developing and applying advanced AI and machine learning techniques to analyse large-scale ecological and environmental datasets. The research aims to improve understanding of biodiversity patterns, ecosystem dynamics, and conservation strategies, supporting evidence-based decision-making for environmental management and policy.
The successful candidate will join a collaborative and internationally recognised research environment, working alongside experts in environmental science, artificial intelligence, and data analytics. The programme offers comprehensive research training, access to cutting-edge computational resources, and opportunities to engage with academic, governmental, and industry partners.
The studentship provides full financial support, including tuition fees and a tax-free stipend aligned with UKRI rates, along with additional funding for research expenses, training, and conference participation.
Eligibility Criteria
- Applicants should hold, or be expected to obtain, a first-class or upper second-class honours degree (or equivalent) in a relevant discipline such as Ecology, Environmental Science, Data Science, Computer Science, Mathematics, or a related field
- A Master’s degree in a relevant subject is desirable but not essential
- International applicants are eligible, subject to meeting English language requirements
Required Expertise/Skills
- Strong quantitative and analytical skills
- Interest or experience in artificial intelligence, machine learning, or data science
- Programming experience (e.g., Python, R, or similar)
- Interest in biodiversity, ecology, or conservation science
- Ability to work independently and collaboratively in interdisciplinary teams
- Strong communication and research skills
Salary Details
- Fully funded studentship
- Tuition fees covered (Home and eligible International candidates)
- Tax-free stipend at the UKRI rate
Application Deadline
- 30 June 2026