PhD Position in High-Resolution Mapping of Fuel Loads, Fuel Moisture, and Microclimates for Wildfire Risk Assessment KU Leuven in Belgium

The sGlobe lab at KU Leuven, in collaboration with PXL BIO-Research, invites applications for a fully funded PhD position as part of the FireRisk project: “High-Resolution Mapping Fuel Loads, Fuel Moisture and Microclimates for Next-Generation Wildfire Risk Assessment.” This interdisciplinary project aims to develop advanced fire weather products by integrating ecological field measurements, drone and airborne LiDAR, satellite remote sensing, and artificial intelligence to create near-real-time, high-resolution maps of fuel loads, live fuel moisture content, microclimate conditions, and fire weather indices across Flanders.

The successful candidate will join the division Forest, Nature and Landscape at KU Leuven, working within a dynamic team of ecologists, remote sensing specialists, fire scientists, and AI researchers. The sGlobe lab focuses on understanding the effects of global change on biodiversity and terrestrial ecosystem functioning, using big data, state-of-the-art modelling, fieldwork, and drone imagery. PXL BIO-Research contributes expertise in risk management, ecosystem modelling, and UAV-based fuel type modelling.

The PhD research will address three main themes: (1) mapping fuel loads across landscapes using airborne and UAV LiDAR, field inventories, and satellite imagery, leveraging deep learning (CNNs) to upscale local measurements; (2) quantifying and predicting live fuel moisture content (LFMC) by combining field data, Sentinel-1 and Sentinel-2 imagery, topographic variables, and advanced machine learning, including multimodal foundation models for Earth observation; (3) developing high-resolution models of microclimate temperature and humidity using logger networks, UAV-derived data, weather observations, and satellite imagery, with AI-based models to predict local conditions and integrate them into fire weather indices like FWI and HDWI.

The project involves intensive fieldwork, drone-based data collection, geospatial analysis, machine learning, remote sensing, and ecological modelling. The resulting workflows and datasets will support improved wildfire forecasting and decision-support tools for land managers and policymakers. The candidate will have access to state-of-the-art UAV platforms, LiDAR systems, high-performance computing, and environmental monitoring networks.

The position offers a full-time PhD fellowship for 4 years, with a competitive salary according to KU Leuven scales, ecocheques, bicycle and allowance or full reimbursement of public transport for commuting, holidays, and bonuses. The preferred start date is November 2026. The successful candidate will be based in Leuven, Belgium.

Applicants must hold or expect to obtain an MSc degree in a relevant field (e.g., Ecology, Biology, Bioscience Engineering, Environmental Sciences, Physical Geography, Remote Sensing) by the start date, have excellent grades, a strong interest in biodiversity and ecosystem functioning, background in terrestrial ecology and ecological modelling, solid programming skills (e.g., R), experience with remote sensing and spatial data analysis, and fluency in English. Interest in UAVs is an asset. Strong communication and teamwork skills are required.

To apply, send your CV and application letter (including your approach to the project and at least one reference) to Prof. Koenraad Van Meerbeek at [email protected] by 30 July 2026. Selected candidates will be notified for interview in mid-August, with interviews held at the end of August 2026. For more information, visit www.sglobelab.com or contact Dr. Sam Ottoy at [email protected].