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Jesús Aguirre Gutiérrez

Top university

1 year 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 flag

Country

United Kingdom

University

University of Oxford

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Keywords

Computer Science
Machine Learning
Epidemiology
Ecology
Environmental Science
Biology
Remote Sensing
Geography
Artificial Intelligence
Population Health
Rainforest Ecology
Climate Dynamics

About this position

If you are interested in this PhD position, you think you fulfill the criteria for the position and you are hard worker, wild thinker and independent, go ahead and apply!
The application window is closing soon.

???? Fancy doing a DPhil at the University of Oxford?

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.

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Professors

Titular Associate Professor and NERC Fellow

University Name
Country flag

United Kingdom

Research Interests

Ecology

Conservation Biology

Plant Ecology

Rainforest Ecology

Climate Dynamics