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

Overview

This doctoral research opportunity focuses on integrating environmental sensing, computational modelling, and data analytics to examine how climate change, wildfires, and land-use changes impact tropical forest microclimates, specifically using Amazonian forests as a test case. The project addresses the critical need for measurements and models operating at fine scales where trees experience environmental stress.

The research is structured around four primary objectives that include evaluating sensor performance and uncertainty, validating physics-based models of energy, heat, and water exchange, combining in-situ measurements with satellite and airborne remote sensing using machine learning, and upscaling these findings to landscape-level predictions with quantified uncertainty. The successful researcher will become part of an international UK and Brazil research team based at the University of Exeter.

What you get

The studentship provides coverage for tuition fees along with an annual stipend of £21,805 for the 2026/7 academic year. The doctoral candidate will receive training in sensor design and calibration, statistical and physics-based modelling, machine learning, high-performance computing in Python and R, geospatial analysis, and reproducible research practices. Additionally, the project provides an opportunity for an industry placement with a sensor partner supporting prototype testing, as well as potential fieldwork in Brazil, subject to obtaining necessary research permits.

How to apply

Candidates have the flexibility to shape the project to emphasize data science, modeling, or sensor development depending on their specific interests. The project can also be completed as a desk-based study utilizing existing data and ongoing collections by partners across Amazonia if fieldwork is not undertaken.

Key dates

The closing date for applications is 2026-12-08.