Fully funded PhD

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

Uni Zürich

Institution
Uni Zürich
Position type
PhD
Location
Zürich, CH
Funding
Fully funded position

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About this position

Über die Stelle

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!

Aufgaben

  • 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.

Anforderungen

    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.

Ausbildung

University

Benefits

Our employees benefit from a wide range of attractive offers. Find out more: https://www.uzh.ch/de/explore/work.html.

Apply directly to Uni Zürich

Emerging Scholars Council is not the employer and does not recruit for this position. It is advertised by Uni Zürich, and your application goes to them. We help students prepare and strengthen their applications.

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