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. Development and integration of state-of-the-art machine learning techniques in the analysis and event reconstruction will be a major component of this work. - Characterization of silicon detection modules using
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. This Post Doctoral position is part of the SilentPitch ANR project which involves a puri-disciplinary team of researchers including machine learning, speech science, cognition and behavioural studies
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ANR project which involves a puri-disciplinary team of researchers including machine learning, speech science, cognition and behavioural studies. This Post Doctoral position will be co-supervised by
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lie at the crossroads of multiple disciplines and involve expertise in optics, electronics, image and data processing (including machine learning), photophysics, chemistry and biology. The position is
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computational fluid dynamics. • Experience in modeling, uncertainty quantification, or statistical methods. • Experience in data science or machine learning is considered an asset. • Experience with high
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experience in large-scale structure simulations, working knowledge of applications of machine learning techniques in cosmology and/or astrophysics (in particular simulation-based inference), strong programming