PhD Environmental Intelligence

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Tuition fee
Apply by
Start date
Sep 2025
Sep 2026
Duration
Campus
Mode of study
Fees and deadlines depend on the selected options. Fees and currency conversion are approximate.
Offer response
4 - 6 weeks after your application is submitted
Backlogs accepted
This course accepts backlogs

Research overview

Environmental Intelligence

The PhD in Environmental Intelligence programme is delivered by the UKRI Centre for Doctoral Training in Environmental Intelligence (CDT EI). The programme pioneers new research in using Data Science and Artificial Intelligence to understand the complex interactions between the environment, climate, natural ecosystems, human social and economic systems, and health.

The increasing availability of large and complex data sets from diverse sources (e.g. environmental monitoring; satellite remote sensing; climate modelling; electronic medical records; social media; and contributions from citizen science) presents an exceptional opportunity to transform our understanding of both the effects of environmental change and our planet-transforming power.

The programme is led by Professor Gavin Shaddick and a team of world-leading researchers, and students will have the opportunity to engage with over 250 researchers at Exeter working in Data Science, AI, and environmental and sustainability research.

Careers

You will have the opportunity to work with the CDT’s external partners, including the Met Office, and a range of international institutions and businesses, to ensure that you are well versed in both cutting edge methodology and on-the-ground policy and business implementation. During your PhD there will opportunities for placements with our partners and to participate in the Alan Turing Institute’s PhD enrichment programme. Overall, the programme offers will allow you to develop skills highly sought after by employers, while also giving you the opportunity to create a professional network with employers.

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Requirements

The requirements may vary based on your selected study options.





















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Use our magical AI system, to check your admission chances for this course.
Tuition fee
Apply by
Start date
Sep 2025
Sep 2026
Duration
Campus
Mode of study
Fees and deadlines depend on the selected options. Fees and currency conversion are approximate.
Offer response
4 - 6 weeks after your application is submitted
Backlogs accepted
This course accepts backlogs