PhD position: Multi-temporal forest canopy height reconstruction from satellite data

Process and analyse large archives of optical stereo satellite imagery. Develop and improve photogrammetric workflows for DSM and CHM generation. Generate and validate multi-temporal canopy height models. Analyse long-term forest structural dynamics and disturbance processes. Publish research results in peer-reviewed journals and present them at international conferences. Contribute to teaching activities within the Department of Geography.

The University of Zurich, Switzerland's largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education.

• You hold a MSc degree in photogrammetry, remote sensing, geomatics, geodesy, physical geography, environmental sciences, computer science, geoinformatics, aero/astro engineering, or a related discipline.

• Experience or strong interest in at least one of the following: Satellite or airborne remote sensing data processing/analysis, Stereo photogrammetry and/or SfM software (open-source or commercial), Very-high-resolution commercial satellite image processing and/or analysis, Airborne LiDAR, and/or spaceborne laser altimetry (GEDI, ICESat-2) analysis, Geospatial data processing, Scientific programming (Python, R, Julia, or Matlab)

• Other relevant, but optional experience (ideally one or more): Point cloud processing and/or analysis, Computer vision and/or machine learning involving geospatial data, Forest science, Linux, Git/Github, Jupyter, Cloud computing, Open-source geospatial stack (e.g., GDAL, PDAL, GeoPandas, xarray), Excellent written and oral communication skills (publication or other technical writing, conference poster or talk)