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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
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control engineering, optimization algorithms Control of drones and flight experiments as well as knowledge in AI / Machine Learning would be an asset Outstanding academic records Teamworking experience, e.g
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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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the computational dosimetry framework for interventional procedures such that it can be implemented in hospitals. With current artificial intelligence (AI) technologies, and particularly machine learning (ML
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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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of the electromechanical aspects of industrial machines, with an emphasis on Industry 4.0 technologies such as machine vision, AI or digital twins. A digital twin can be defined as a virtual replica of a physical system
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models combining machine learning, and physics-of-failure (PoF) approaches using in-situ data • You work on projects independently • You will present your work at international conferences and
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Python or R A willingness to learn and apply machine learning approaches We offer A versatile and challenging job in a vibrant and world-class research environment operating at an international level
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support tasks for the Bittremieux Lab, such as assisting in practical teaching sessions and supervising Bachelor and Master students. Profile You hold a Master degree in Computer Science, Machine Learning
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, mathematics or a related domain. You have a solid academic track record, at least at the cum laude level. You are interested in both Machine Learning and Symbolic/Logic-based AI methods. You strive