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postdoctoral research project. The project focuses on the development and application of a remote sensing algorithm for monitoring the physicochemical properties of aerosols based on optical measurements taken
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atmospheric sciences • Knowledge of cloud or aerosol physics • Experience in algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a
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, retrieval algorithm, applications in hydrology) and will benefit from their knowledge and experience on the mission. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5126-ARNMIA-005
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functional molecular or nano-scale systems that can be remotely controlled, notably by light. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7053-PHIPIE-002/Candidater.aspx Requirements
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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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analysis of in situ measurement data and spatial remote sensing data - Participation in the scientific supervision of students - Participation in national and international mobility programs The project is
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. Atmospheric measurements (in situ and remote sensing) provide a robust method to assess and improve emission inventories and to monitor the effectiveness of reduction measures. The project will develop
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in the use and exploitation of high spatial and temporal resolution remote sensing data. An interest in causal discovery and inference is more than welcome. The candidate will be required to interact
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climate and geospatial databases. Experience in GIS/Geomatics and remote sensing data analysis. • Languages: French and English (spoken and written) are essential, given the regional context and
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characterize the spatio-temporal contexts that favor crises. • Development of advanced predictive models (multivariate approaches, machine learning) combining event data, snow and weather data, and remote