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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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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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cells, embryo models and human embryos, with a focus on understanding how cell stress impacts these processes. During your PhD, you will work very closely with a postdoctoral fellow that will be carrying
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pathway. Additionally, finite element theoretical modelling and density functional theory calculations will be used to further increase our understanding of the photo-reduction mechanism. Correlating
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are linked to research on composite hydrogen tanks, composite propellers for drones and finite element modelling of textile manufacturing. All research will be conducted with leading companies in
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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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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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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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(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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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