PhD Position in Machine Learning and Remote Sensing for Industrial Plume Inversion

A PhD position is available in the field of machine learning and remote sensing, focusing on the inversion of industrial stack plumes from satellite images. The project aims to leverage generative models to improve the characterization of pollutants emitted by industrial sites such as steel plants and coal-fired power stations. This research is highly relevant to public health, as accurate pollutant monitoring is crucial for environmental safety and regulatory compliance. The PhD will be based in Toulouse at ONERA, the French Aerospace Lab, and will be supervised by Romain Thoreau (Assistant Professor, AgroParisTech), Pierre-Yves Foucher (ONERA), and Camille Desjardins (CNES). The work is at the intersection of computer science, environmental science, and advanced data analysis, offering opportunities to collaborate with leading French research institutions. Applicants should have a strong background in machine learning and remote sensing, with experience in generative models, satellite image analysis, or environmental data analysis considered a plus. A relevant master's degree in computer science, engineering, or a related field is expected. Good communication and teamwork skills are also desirable. For more information and the full position description, visit the provided link. This is an excellent opportunity for candidates interested in applying advanced computational methods to real-world environmental and public health challenges.