Postdoc in Data-driven methods for remote sensing of forests using the Biomass satellite
Description
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Chalmers tekniska högskola
Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the post-doc position for you!
brings together expertise in space, geoscience, energy and sustainability. Through curiosity-driven research, education and collaboration, we explore the Universe, the Earth and the complex systems linking environment, energy and society
- enabling knowledge-based solutions for a sustainable future.
At, we develop advanced methods and instruments to observe and understand the Earth system. Combining satellite, airborne and ground-based measurements with modelling and machine learning, we collaborate globally to monitor environmental change and support a sustainable future.
About the research project
The Biomass satellite carrying the ground-breaking P-band synthetic aperture radar (SAR) was launched on 29 April 2025 and recently finished its commissioning phase. This 5-year ESA Earth Explorer mission will produce much-needed global forest biomass data using its polarimetric and tomographic radar capabilities. Our team is responsible for the algorithms which derive the biomass data product.
The post-doc project is about extending the biomass algorithm to also include data-driven, machine learning approaches. The biomass data product will be validated by data from an international network of ground-truth forest sites (GEO-TREES, geo-trees.org). The developed algorithms thus extend and complement the current generation of the biomass data product. A large-scale training data set will be generated for the biomass algorithm. The training data will be based on other remote sensing data which estimate forest biomass, e.g. from airborne and spaceborne laser scanners, since no in-situ based biomass data with global coverage exist.
Who we are looking for
The following requirements are mandatory:
The following experience will strengthen your application:
What you will do
The position is meritorious for future roles in academia, industry, or the public sector.
Contract terms
The position is a temporary full-time employment for three years.