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), consists of two main parts. First, the candidate will develop machine learning models aimed at improving the follow-up of neurocognitive function in critically ill children after discharge from the intensive
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biomass remote sensing, crop modeling, data assimilation and machine learning Supervise master thesis students For PhD students: follow training in line with the doctoral school requirements Where to apply
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combine EMI footprints, which capture normal variations through characteristic curves and statistical distributions, with state-of-the-art machine learning and deep learning techniques (e.g., one-class
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