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heavy-duty transport. This is an opportunity to measure, characterize, model and understand the formation of brake wear particles and ultimately reduce the health impact from urban transport. The research
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your application: Superb writing skills Experience with high-throughput simulations and materials databases Advanced heat transfer modeling, especially for TIMs and nanostructures A strong
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of surface sites makes theoretical understanding difficult. This project will develop and benchmark machine learning models to predict local electronic density of states (DOS) at alloy catalytic sites
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of quick clays. A novel combination of miniaturised thermal-hydro-mechanical experiments and particle level modelling will be pursued to unravel the unique mechanisms that make quick clays so hazardous and
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to emerging digital technologies Interplay between technology development and business model evolution - how advancements in technologies reshape value creation and value capture, necessitating continous
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of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments and real-life monitoring to support our findings. Besides research, our division is actively involved in
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environments ensure safe operations Our activities are primarily related to the development and application of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments
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different mixing and reactive properties compared to conventional fuels. In this project, turbulent mixing and combustion of hydrogen in air will be studied through optical experiments and numerical modelling
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in fluid dynamics, turbulence modeling, CFD, and turbomachinery. Experience with CAD and CFD tools (e.g., Ansys Fluent, CFX, StarCCM+, OpenFOAM). Programming skills (e.g., Python, MATLAB). Knowledge
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introduces new and underexplored vulnerabilities to network-based threats. The goal of this research is to uncover such threats, evaluate their impact on training performance and model integrity, and develop