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combining space-based remote sensing and modeling, it aims to better understand the evolution of forest fuels and their role in fire propagation. Tested on pilot forest areas (Centre-Val de Loire and Pyrénées
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for calibrating remote sensing instruments and validating national and regional aerial biomass maps. The One Forest Vision initiative (OFVi project, https://www.oneforestvision.org/eng ) has enabled the creation
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algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a team • Proficiency in programming languages (e.g. Python, R, Fortran
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Eligibility criteria . PhD in atmospheric sciences • Knowledge of cloud physics • Experience in algorithm development and satellite remote sensing • Good written and spoken English • Ability to work
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a public research laboratory which aims to better understand the functioning of continental surfaces and their interactions with climate and humans. Remote sensing is heavily used by Cesbio scientists
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programming. - Interest in natural hazards, particularly gravitational processes. - Doctoral and/or post-doctoral experience in one or more of the following fields: remote sensing, geophysics, natural hazards
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carried out under the scientific supervision of Marianne Laslier (UMR EDYSAN 7058 CNRS), lecturer and researcher in ecology, geography, and remote sensing; Pauline Dusseux (UMR PACTE 5194 CNRS), lecturer
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, 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
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modelling. Furthermore, better knowledge of these properties helps refining the interpretation of data obtained from both active and passive remote sensing. PhD Topic This PhD project aims to quantitatively
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will benefit from the various skills in tropical ecology, vegetation modelling, and remote sensing of a large and enthusiastic team of collaborators. Where to apply Website https://emploi.cnrs.fr