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, followed by post-plasma catalysis into C2H4; (2) fully coupled modelling (i.e., plasma fluid dynamics and plasma + catalyst surface chemistry) for plasma-based CH4 conversion with post-plasma catalysis
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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of a doctorate, contains: Are you eager to improve pandemic preparedness through data-driven research? Do you want to work on real-world implementation of AI and epidemiological models in healthcare
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improve the efficiency, maneuverability, and noise performance of drones and other multirotor aircraft, but their deployment requires more advanced modeling and control methods. The PhD will focus
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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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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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partially filled containers – is a major challenge in aerospace, transport, and energy systems, where it can compromise stability and safety. The PhD will focus on developing low-order models of sloshing
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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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mobility of migrants shape local populations? Developing a spatial microsimulation model of population dynamics with application in infectious disease modelling (DynaMIGs)”. DynaMIGs is a four-year
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will transition in a second phase to white box approaches that result in interpretable models. For ground truth data, μCT data will be used. A similar approach will be applied using surface roughness