Eidg. Forschungsanstalt WSL
Birmensdorf
Scientific Staff Member for Remote Sensing and Machine Learning for Modelling Drought-Related Forest Damage
- 16 June 2026
- 100%
- Birmensdorf
About the job
The Swiss Federal Institute for Forest, Snow and Landscape Research WSL, with around 600 employees, is part of the ETH domain. It is concerned with the sustainable use and protection of the environment as well as responsible management of natural hazards.
Scientific Staff Member for Remote Sensing and Machine Learning for Modelling Drought-Related Forest Damage
The Forest Resources and Forest Management research unit records and analyses changes in the landscape and forest. In the Forest-LENS project, we investigate drought symptoms in beech stands. The basis is an already developed Sentinel-2 and machine learning-based processing pipeline for detecting such symptoms, which will be spatially and methodologically expanded. A particular focus is on the influence of forest structure on the drought resilience of beech. For this purpose, we combine satellite-based drought indicators with forest structure information derived from LiDAR data as well as other environmental and site data. The position is affiliated with the GIS research group and we are looking for a candidate for a duration of two years starting immediately or by arrangement.
You hold a completed doctorate in environmental sciences, forestry, or remote sensing and have proven experience as a data scientist. We also expect very good knowledge in spatial modelling with machine learning, solid experience in processing Sentinel-2, PlanetScope, and LiDAR data, as well as in-depth knowledge in modelling drought symptoms in forest ecosystems. Excellent programming skills in Python and experience handling large raster and vector datasets are required. Furthermore, you describe yourself as a committed, independent, and meticulous person who implements complex spatial analyses purposefully and prepares your results understandably for science and practice. You communicate fluently in English and German (at least at B1 level) and have experience in scientific publishing.
Please send your complete application to Beatrice Lamprecht, Human Resources WSL, by submitting the required documents via our application portal. Applications by email or post will not be considered. For questions, Andri Baltensweiler (andri.baltensweiler@wsl.ch) will be happy to assist you. At WSL, diversity and inclusion are lived values. We are committed to gender equality and promoting an open and inclusive working environment.
