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and machine learning applied to data fusion and adapt them to the field of exoplanet characterization. They will develop and maintain the FORMOSA code in coordination with the team of students working
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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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ExperienceNone Additional Information Eligibility criteria - Holding a doctoral degree in particle physics - Experience in C++ and Python programming is desired - Experience in training and using Machine Learning
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standard Python libraries for machine learning, in particular PyTorch. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR6072-DAVTSC-008/Default.aspx Work Location(s) Number of offers
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on the plants Arabidopsis thaliana will generate maps of depolarization, retardance, dichroism, and optical axis azimuth, which will feed machine learning models developed by the project partners to identify
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a