Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Delft University of Technology (TU Delft)
- Nature Careers
- Technical University of Munich
- CNRS
- Forschungszentrum Jülich
- Norwegian University of Life Sciences (NMBU)
- Delft University of Technology (TU Delft); Delft
- Delft University of Technology (TU Delft); today published
- Delft University of Technology (TU Delft); yesterday published
- Loughborough University
- Leibniz
- Loughborough University;
- Newcastle University
- UiT The Arctic University of Norway
- University of Göttingen •
- Wageningen University & Research
- ;
- AI & Cyber Futures Institute - Charles Sturt University
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- DAAD
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- GFZ Helmholtz Centre for Geosciences
- IDAEA-CSIC
- IRTA
- Instituto Superior de Agronomia
- Instituto de Ciencias del Patrimonio - Spanish Council for Scientific Research (CSIC)
- KU LEUVEN
- Lulea University of Technology
- Max Planck Institute for Biogeochemistry •
- McMaster University
- Multiple
- National University of Science and Technology POLITEHNICA Bucharest
- Queensland University of Technology
- Radboud University Medical Center (Radboudumc)
- The University of Alabama
- The University of Newcastle
- Tilburg University
- University of Bremen •
- University of Cambridge;
- University of Plymouth;
- University of Sheffield
- Université Savoie Mont Blanc
- Wageningen University and Research Center
- Wetsus - European centre of excellence for sustainable water technology
- 34 more »
- « less
-
Field
-
, 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
-
, Geoscience, Remote Sensing, Hydrology, Data Science, Physics, or related fields • Experience in machine learning (ML), artificial intelligence (AI) or related fields • Software skills in ML languages such as
-
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
-
research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic
-
, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management. Click here to go to the website of the Faculty of Civil
-
and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management. Click here to go to the website of the Faculty of Civil Engineering & Geosciences. Conditions of employment
-
to remote sensing and simu-lation modeling. A particular focus of our work is on mountain forest ecosystems. A quantitative understanding of ecosystem dynamics provides the foundation for the development
-
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
-
Master’s degree in machine learning, computer science, or a forest-related field with a focus on remote sensing Experience with deep learning The following experiences and skills will be emphasized
-
, 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