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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
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(Artificial Intelligence and Epidemic Modeling to Prepare Hospitals for the Next Respiratory Pathogen with Pandemic Potential). Project Overview The COVID-19 pandemic exposed critical gaps in our ability
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FLOW research group is a young, dynamic group working in the fields of thermodynamics, fluid mechanics, and data-driven modelling. At the Department of engineering Technology (INDI) — Thermo and Fluid
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-hydrated alkali-silicate melts that enable efficient zeolite formation under mild conditions. Molecular modeling and experimental characterization show that the type and concentration of the alkali cation
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. System Modeling: Develop and refine photonic system models incorporating key quantum mechanisms. Use simulation tools (Lumerical, Synopsys, Matlab, Python, …) to validate architectural feasibility and
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data collected from a geothermal borefield in Brussels, modelling activities of subsurface heat transfers between borehole heat exchangers, and the development of strategies for the optimal integration
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operational employment. This doctoral research will thus leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modelling systems as graphs
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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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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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