PostDoc Habitat Mapping 80-100% (m/f/d)
Eidg. Forschungsanstalt WSL
Birmensdorf
Key information
- Publication date:04 September 2025
- Workload:80 – 100%
- Place of work:Birmensdorf
Job summary
Join the ETH Zurich-affiliated WSL, focusing on environmental sustainability. This is a great opportunity for collaborative research and innovation.
Tasks
- Create nationwide habitat distribution maps using field and remote sensing data.
- Utilize SDMs and AI methods for image classification and model updates.
- Collaborate with a small team to publish results and integrate findings.
Skills
- PhD in environmental sciences, remote sensing, or related field required.
- Experience in spatial modeling and machine learning essential.
- Strong statistical skills and proficiency in R or Python needed.
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The Swiss Federal Institute for Forest, Snow and Landscape Research WSL, with around 600 employees, is part of the ETH domain. It deals with the sustainable use and protection of the environment as well as responsible management of natural hazards.
PostDoc Habitat Mapping 80-100% (m/f/d)
The Landscape Dynamics research unit investigates patterns and processes of land systems and their dynamics at various spatial and temporal scales. The Remote Sensing group is looking for a 2-year position within the BAFU-funded project "Habitat Map Switzerland"
You will create nationwide distribution maps of habitat types/ecological communities. You will integrate field data, remote sensing data, and other auxiliary data into spatial modeling processes, applying techniques such as SDMs and artificial intelligence methods for image classification including machine learning and deep learning. Furthermore, you will develop clear and documented workflows that enable regular updates of the derived models and maps. You will work closely with a small team to integrate your maps into a nationwide habitat map and jointly publish the results.
You hold a doctorate in environmental sciences, remote sensing, computer vision, or a comparable field. You have experience in spatial modeling of habitats using machine learning and the use of large-scale earth observation data. Experience with artificial intelligence methods for image classification is an advantage (e.g., CNN). Solid ecological knowledge of the characteristics of communities and habitats in Switzerland is beneficial. You are proficient with statistical methods and scripting languages (e.g., R, Python). You are highly motivated to analyze data with advanced methods and tools. Good communication and organizational skills, a strong team spirit, and fluent English skills are required; very good German or French skills are an advantage.
Please send your complete application to Beatrice Lamprecht, Human Resources WSL, by submitting the required documents via our application portal. Applications by email or postal mail will not be considered. For questions, Dr. Bronwyn Price is available at Tel. +41 (0)44 739 28 19. Diversity and inclusion are lived values at WSL. We are committed to gender equality and promoting an open and inclusive working environment.
