Livia Piermattei
1 month ago
PhD in Earth Observation, AI, and Computer Vision for Forest Canopy Height Reconstruction University of Zurich in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Aug 16, 2026
Country
Switzerland
University
University of Zurich
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About this position
University of Zurich is recruiting three PhD candidates for an SNSF-funded project on forest canopy height reconstruction from satellite data. The positions are part of the project “From Alps to Arctic: Satellite-based Assessment of Forest Canopy Height across Decades”, jointly led by Prof. Livia Piermattei (Remote Sensing of Environmental Changes Group, Department of Geography) and Prof. Jan Dirk Wegner (EcoVision Lab, Department of Mathematical Modeling and Machine Learning).
The research combines earth observation, remote sensing, AI, computer vision, and machine learning to reconstruct forest change across the Alps and Arctic using modern and historical satellite imagery. Topics include deep learning for satellite image time series, self-supervised and multimodal learning, domain adaptation, super-resolution of historical imagery, photogrammetry, laser altimetry, uncertainty estimation, and forest change analysis.
This specific advertised PhD position focuses on reconstructing forest canopy height models from optical stereo satellite imagery across alpine and boreal forests. The project uses archives such as SPOT-5, Pléiades, WorldView, ArcticDEM, ICESat-2, GEDI, and airborne LiDAR to generate multi-temporal DSMs and CHMs spanning more than two decades, and to study long-term forest structural dynamics, disturbance, growth, loss, and regeneration.
Eligibility: MSc degree in photogrammetry, remote sensing, geomatics, geodesy, physical geography, environmental sciences, computer science, geoinformatics, aero/astro engineering, or a related field. Strong interest or experience in remote sensing data processing, stereo photogrammetry/SfM, VHR satellite imagery, LiDAR or laser altimetry, geospatial data processing, and scientific programming is expected. Experience with point clouds, computer vision, machine learning, Linux, Git, Jupyter, cloud computing, and open-source geospatial tools is a plus.
Funding: Fully funded 4-year PhD position. The project provides access to unique datasets, computational resources, and collaboration with researchers across Europe and Canada.
Application: Apply via the UZH job portal with a cover letter, CV, publication list (if any), master certificate, master thesis or draft, and contact details for two referees. Applications are reviewed from 17 August 2026 until the position is filled. Start date is 1 January 2027 or by agreement.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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