Ph.D. position at LaSTIG: A scholarship opportunity is available for a Ph.D. position in the field of large-scale 3D reconstruction of forest canopies using aerial and satellite imagery. The research aims to develop a novel multi-view stereo matching method tailored for precise and robust prediction of forest canopy surfaces. The project addresses challenges such as geolocation inaccuracies, complex surface reflectance, and the lack of benchmark datasets for comparison.
Large-scale 3D Reconstruction of Forest Canopy from Aerial and Satellite Imagery
Summary Table:
| Study Area | Computer Science, Applied Mathematics, Photogrammetry, Remote Sensing |
|---|---|
| Scholarship Description | Developing a multi-view stereo matching method for 3D forest canopy reconstruction |
| Eligibility | Master’s 2 student in relevant fields, proficiency in Python/C++, deep learning, and aerial/satellite image processing |
| Required Documents | CV, Letter of Motivation |
| How to Apply | Send documents to ewelina.rupnik [AT] ign.fr, marc.pierrot-deseilligny [AT] ensg.eu |
| Last Date | Rolling Deadline, Apply ASAP |
Study Area: Computer Science, Applied Mathematics, Photogrammetry, Remote Sensing
Scholarship Description: The Ph.D. project focuses on the development of a novel multi-view stereo matching method for 3D surface reconstruction of forest canopies using aerial and satellite imagery. The project addresses challenges related to surface reflectance, geolocation inaccuracies, and the need for benchmark datasets.
Eligibility: Candidates should be Master 2 students in computer science, applied mathematics, photogrammetry, or remote sensing. Proficiency in Python and/or C++, previous experience in deep learning, and optional experience in aerial/satellite image processing are desired.
Required Documents:
- CV
- Letter of Motivation
How to Apply: Send the required documents to ewelina.rupnik [AT] ign.fr and marc.pierrot-deseilligny [AT] ensg.eu.
Last Date: Rolling Deadline, Apply ASAP
