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

### 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.