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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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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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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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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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or altered behavioral responses in ASD models How these changes reflect underlying shifts in cortical circuit function You will work within the Bonin and Farrow Labs, which brings deep expertise in
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or altered behavioral responses in ASD models How these changes reflect underlying shifts in cortical circuit function You will work within the Bonin and Farrow Labs, which brings deep expertise in
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Genetics, Reproduction and Development (GRAD) Large Research Group to: Use single-cell omics techniques to analyze human pluripotent stem cells, human embryos, and stem cell-derived embryo models. Study how
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the immune response to mpox in both animal models and in vitro systems. We are looking for a motivated PhD student to help advance this line of research. As a PhD student, you will: Design and conduct
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for anomaly Detection and diagnostics: Leveraging state-of-the-art machine learning and deep learning models for automated fault detection, classification, and time-till-failure prediction. This will involve