PhD position: Multi-temporal forest canopy height reconstruction from satellite data 80 %

Description du poste

### 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. Put your talent and skills to work with us. Find out more about UZH as an employer! ### Your responsibilities * 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. Your profile 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) ## We offer ## * A fully funded 4-year PhD position. * Access to unique international remote sensing datasets. * Project collaboration with leading forest and remote sensing researchers across Europe (such as WSL, TU Wien, NIBIO, and IGE Grenoble) and Canada (Canadian Forest Service). * Excellent research infrastructure and computational resources. * A stimulating and supportive research environment at the University of Zurich. * Opportunity to collaborate with both remote sensing and machine learning research groups at the University of Zurich.