7 machine-learning-modeling-"Linnaeus-University" PhD positions at KU LEUVEN in Belgium
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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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neuromorphic ultra-low-power active sensor readout and processing at the edge. The chip design will enable online learning capabilities, aiming at modulating the spatio-temporal filtering properties with
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military performance, presenteeism, and may even lead to costly evacuations during deployments. This PhD project builds upon pioneering research at MHQA and aims to implement and evaluate allergy screening
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. The core objective is to develop advanced 3-D modelling and optimisation methodologies for magnetic components that enable accurate leakage inductance prediction and improved overall performance. Traditional
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model-based control tailored to systems like NudgeFlow. The framework decomposes the global control problem into smaller local problems for each zone or room, enabling independent optimization with local
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analyse levels of identified proteins in a larger patient population as well as an animal model of the Fontan circulation.• You will use in vitro techniques and immunohistochemsitry on an animal model
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modelling and density functional theory calculations will be used to further increase our understanding of the photo-reduction mechanism. Correlating these theoretical insights with the structure and activity