Jesús Aguirre Gutiérrez
Top university
5 months ago
Environmental Change University of Oxford in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
This Leverhulme-funded studentship covers University fees and a maintenance stipend at least at the standard UK doctoral rate for up to three years. Additional allowances and exact amounts will be confirmed at offer stage. Reasonable research, travel, and fieldwork costs are supported. College membership is provided.
Deadline
Expired
Country
United Kingdom
University
University of Oxford

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About this position
The Environmental Change Institute (ECI) is looking for a brilliant new researcher to join us on a fully funded:
Leverhulme Trust Studentship in AI, Remote Sensing, and Forest Resilience to Climate - Insights for Public Health.
Starting April 2026, you’ll be part of our Biodiversity and Earth Observation (BioEO) group at the ECI at the University of Oxford, using cutting-edge tools to explore how forests respond to climate change — and what that means for people and the planet.
?? Deadline: 7 November 2025
?? Oxford, UK
?? Fully funded, full of opportunity, and definitely not your average PhD.
?? https://lnkd.in/duCZJ3hZ
Funding details
This Leverhulme-funded studentship covers University fees and a maintenance stipend at least at the standard UK doctoral rate for up to three years. Additional allowances and exact amounts will be confirmed at offer stage. Reasonable research, travel, and fieldwork costs are supported. College membership is provided.
What's required
Applicants must have a master's degree with distinction (or at least a distinction grade on the dissertation) in Geography, Environmental or Plant Sciences, Ecology, Remote Sensing, Data/Computer Science, Epidemiology or related fields. A first-class or strong upper second-class undergraduate degree with honours in any discipline is required. Strong quantitative and programming skills (R required; Python desirable), experience with GIS/remote sensing workflows and large datasets, and a clear interest in tropical forest ecology and public health links are essential. Experience with machine learning/deep learning, trait-based ecology, epidemiological modelling, or tropical fieldwork is desirable. Applicants should demonstrate aptitude for computational methods. All standard University of Oxford DPhil application documents are required.
How to apply
Apply through the University of Oxford’s online admission system for the DPhil in Geography and the Environment. Enter Dr Jesús Aguirre Gutiérrez as the proposed supervisor and use the project title provided. Enter reference code '26SOGE01' on the funding tab. Submit all required documents as per the DPhil application instructions.
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