Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nature Careers
- Technical University of Munich
- NTNU - Norwegian University of Science and Technology
- University of Göttingen •
- ;
- CNRS
- Ghent University
- Swedish University of Agricultural Sciences
- ; Swansea University
- AI & Cyber Futures Institute - Charles Sturt University
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Chalmers University of Technology
- Delft University of Technology (TU Delft); Delft
- Forschungszentrum Jülich
- GFZ Helmholtz Centre for Geosciences
- Leibniz
- Loughborough University
- Max Planck Institute for Biogeochemistry •
- Queensland University of Technology
- Technical University of Denmark
- The University of Newcastle
- University of Alberta
- University of Bremen •
- University of Sheffield
- Wetsus - European centre of excellence for sustainable water technology
- Zynthera Company
- 16 more »
- « less
-
Field
-
, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems. See the project website to find out more about the FORFUS doctoral
-
this centre, we are opening a PhD position on remote sensing of mountain forest dynamics. The Technical University of Munich (TUM) is one of the leading universities globally. At the TUM School of Life Sciences
-
The Forest Growth & Yield Lab at the University of Alberta has an open graduate research assistantship at the Ph.D. level in Applied Remote Sensing for assessment of forest resilience, under
-
Management is one of Europe’s leading research groups in the field of Earth observation and remote sensing. Within the project “Assessing the impacts of transient forest edges on biophysical conditions and
-
of surface-atmosphere interactions and limitations in current observational methods . Traditional remote sensing techniques are generally indirect, inferring evaporation from thermal imagery and reflectance
-
, and will work in close collaboration with the FOX team of the CRISTAL laboratory. The LOA team has internationally recognized expertise in the field of radiative transfer and remote sensing. The CRISTAL
-
species, and the emergence of previously unseen classes. Recent advances in remote sensing and machine learning provide new opportunities to address these challenges, but most current approaches
-
processes, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems. See the project website to find out more about the FORFUS
-
engineering/science, remote sensing, computer science). A relevant master’s degree and/or employment experience will be an advantage. English language requirements: Applicants must meet the minimum English language
-
, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems. See the project website to find out more about the FORFUS doctoral