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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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dynamical systems), epidemiological modelling, data analysis (statistics, machine learning). • in scientific programming (preferably Python, Matlab, R) Genuine interest in the analysis and modeling
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researchers with ample experience in MEG/EEG data analysis, BCIs, signal processing, deep learning for brain imaging analysis, biomedical statistics, dynamical systems and research on motor control. The lab has
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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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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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disciplines and involve expertise in optics, electronics, image and data processing using machine learning, photophysics, chemistry and biology. The position is therefore particularly well suited for candidates