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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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laude level. You are interested in both Machine Learning and Symbolic/Logic-based AI methods. You strive for excellence and have a scientific mindset. You are a loyal team player, who can work
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tools Computer science » Systems design Engineering » Chemical engineering Engineering » Computer engineering Engineering » Design engineering Engineering » Industrial engineering Engineering » Materials
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knowledge of wireless communications, and signal processing. You have at least intermediary knowledge of machine learning algorithms, including federated learning, split learning, and graph neural networks
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. Kinetic rates will be calculated on the fly from molecular dynamics simulations using machine learning potentials. This approach will provide guidelines to steer the formation process of zeolites by tuning
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interdisciplinary research team, focusing on human-robot interaction, unconventional robotics, cognitive systems and machine learning. You will have access to the full facilities of IDLab, including high-performance