Title of post-doctorate offer: « Mapping orchard leaf biochemistry from UAV imagery: a hybrid-based approach from 3D radiative transfer modeling and hyperspectral/LiDAR datasets »
This work is part of the ANR CANOP project aiming to assess the health and nutritional status of peach and apricot trees in contrasted input managements and genotypes from (sub)centimeter scale datasets acquired in the laboratory and from UAV optical cameras (https://remotetree.sedoo.fr/canop/).
Keywords: 3D modeling, simulation, sensitivity analysis, machine learning, inversion, radiative transfer, UAV imagery, hyperspectral, LiDAR
Duration: 12 months
Application deadline: 01/12/2026
Start of contract: 01/01/2026
Host laboratory: Department of Optics and Associated Techniques (DOTA) at the French Aerospace Lab (ONERA), Toulouse center
External collaborations: Partner laboratories of the CANOP project (INRAE – EMMAH/TETIS/GAFL/PSH and UT3/CESBIO)
Profile and skills required:
Formation: Engineering schools of optics or physics and/or Master’s degree in physics or applied
mathematics, PhD in remote sensing
Desired Skills: signal / image processing, remote sensing, machine learning, ecology/environment, scientific programming (python), radiative transfer models
If you are interested, please send both a CV and a motivation letter to karine.adeline@onera.fr and sophie.fabre@onera.fr
