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Maclean

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PhD Studentship: Integrating sensing, modelling and data analytics to understand forest microclimate dynamics under fire, degradation and climate change in Amazonia University of Exeter in United Kingdom

Degree Level

PhD

Field of study

Environmental Science

Funding

Available

Deadline

Dec 8, 2026

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Country

United Kingdom

University

University of Exeter

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Keywords

Environmental Science
Remote Sensing
Earth Science
High Performance Computing
ML

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About this position

[Full fees and a stipend of £21,805 per annum for 2026/7.]

This PhD studentship at the University of Exeter focuses on understanding how tropical forest microclimates are changing under fire, degradation, land-use change, and climate change in Amazonia. The project sits at the intersection of environmental sensing, computational modelling, data analytics, and remote sensing, with a strong emphasis on predicting fine-scale climate conditions that influence tree mortality, drought stress, and fire risk.

The research will develop and test an integrated framework for predicting microclimate dynamics in complex, data-sparse environments. Key themes include sensor performance and uncertainty, validation and improvement of physics-based microclimate models, fusion of in-situ sensor data with airborne and satellite observations, and upscaling predictions while quantifying uncertainty. The project uses Amazonian forests as a challenging real-world test case and draws on the UKRI-funded Amazon PyroCarbon Project, which provides extensive environmental sensor networks and field datasets across forests with different fire and land-use histories.

The doctoral researcher will work with established dataloggers, custom-built and prototype devices from an industry sensor partner, and open-source microclimate models developed by Prof Maclean's group. The project also includes data from GEDI/Lidar, optical satellite imagery, and open land-use datasets. The successful applicant can shape the project around their interests, with possible emphasis on sensor development, modelling, or data science.

Training will cover sensor design and calibration, physics-based and statistical modelling, machine learning, geospatial analysis, high-performance computing in R and Python, and reproducible research practice. Fieldwork in Brazil is possible subject to research permits, but the project can also be completed as a desk-based study using existing and partner-collected data. The studentship offers an opportunity to join an international UK–Brazil research team and to contribute methods with relevance beyond tropical forests, including environmental monitoring in agriculture, cities, conservation, and wildfire management.

Funding: The studentship is funded by the EPSRC and provides fees plus a stipend of £21,805 per annum for 2026/7.

Deadline: 2026-12-08.

Funding details

Available

What's required

Applicants should be suitable for PhD study and interested in environmental sensing, modelling and data analytics. The project welcomes backgrounds in sensor development, physics-based or statistical modelling, machine learning, geospatial analysis, high-performance computing, R and Python, and reproducible research. Fieldwork in Brazil is possible but not essential; the project can also be completed as a desk-based study using existing and ongoing partner data.

How to apply

Apply through the University of Exeter funding page using the application link provided. Review the project details carefully and submit your application before 2026-12-08. If you are interested in fieldwork, modelling or data science, highlight that in your application.

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Professors

Prof at University of Exeter

University Name
Country flag

United Kingdom

Research Interests

Environmental Science

High Performance Computing

Remote Sensing

Earth Science

Ml