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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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experience with time series data analysis and/or anomaly detection is a plus. I am proficient in Python and am familiar with data science and machine/deep learning toolkits. As a PhD researcher at KU Leuven, I
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Computational Biology PhD candidate to join our interdisciplinary team, focusing on how developing animal systems self-organize and acquire shapes. In our lab, we work with detailed registrations of embryos over
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of the professors of the Machine Learning group mentioned above, that is, Prof. Jesse Davis, Prof. Luc De Raedt, Prof. Tias Guns, Prof. Giuseppe Marra or Prof. Hendrik Blockeel. You will be part of a dynamic team