Wildfires have significant socio-economic and ecological impacts, posing risks to human lives, buildings, ecosystem services and biodiversity values. In Europe, areas with increased danger are being pushed north by climate change. Even though many industrialized countries have implemented fire management strategies, formal risk assessment systems are lacking in many regions, including Flanders. Pan-European initiatives are hampered by coarse spatial resolution, often underestimating local fire dynamics and overlooking the need for region-specific assessments. Without this locally contextualised accuracy, the reliable prediction of fire propagation and optimization of resource deployment remains severely constrained.
Five PhD students will perform research to meet FireRisk’s core objectives:
- the development of a locally calibrated fire spread model that accounts for land management and design scenarios (PhD 1)
- the generation of near-real-time, high-resolution maps of fuel loads, fuel moisture, microclimate conditions, and fire weather indices for improved wildfire risk assessment and management (PhD 2)
- understanding how land management and landscape design influence wildfire risk and post-fire ecosystem resilience (PhD 3)
- the translation of scientific outputs into actionable frameworks for both operational decision-making and long-term governance (PhD 4)
- the enhancement of first responder training through high-fidelity 3D visualization (PhD 5).
The vacant research position corresponds to the abovementioned ‘PhD 1’ in the FireRisk project. More specifically, you will combine spatial data science with environmental modelling to generate the first high-resolution assessment of the Wildland-Urban Interface (WUI) and wildfire risks in Flanders. During the first year, you will analyse high-resolution geodatasets and collaborate with various stakeholders to establish locally tailored definitions and maps of interface and intermix WUIs where human infrastructure meets natural vegetation. In the subsequent years, you will combine these insights with predictive modelling and select, train, and validate process-based or deep-learning fire propagation models using a.o. detailed information about topography, meteorology, and historical fire events. Ultimately, you will use this model to simulate various land management scenarios and mitigation measures, translating complex spatial data into an actionable decision-support tool for regional fire prevention and climate resilience.
The position requires strong quantitative and programming skills (R or Python), experience with spatial and ecological modelling, and the ability to work with large datasets. You will collaborate with the FireRisk-consortium (including the other PhD researchers) and international partners.
You will conduct research, write and publish scientific articles, actively participate in international and national congresses/meetings and participate in the doctoral school of Sciences and Technology, with the aim of writing a doctoral dissertation.
The Centre for Environmental Sciences (CMK) is a multidisciplinary research institute bringing together 227 researchers from 38 nationalities across six research groups. CMK focuses on fundamental and applied environmental research, as well as industrial collaboration, to address complex societal challenges that require interdisciplinary approaches. Research at CMK spans multiple domains, including understanding environmental influences on organisms, developing and assessing sustainable technologies to mitigate environmental impacts, and monitoring biodiversity and ecosystem services under stress conditions such as climate change.
You will be appointed and paid as PhD student.
We offer you a two-year PhD scholarship, which will be extended for another two years, subject to a positive intermediate evaluation by the doctoral committee. The preferred starting date is October or November 2026. The successful candidate will be based at the Center of Environmental Sciences. You will be part of a young and dynamic international scientific team, where work-life balance is important.
The selection procedure consists of a preselection based on application file and an interview.
Submit an application letter and CV with your application. A notification of selection for interview can be expected in the second half of August. The interviews (online or in person) will take place in August and September 2026.
