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for inclusive eHMIs. Design accessible VR simulators for people with disabilities. Conduct VR experiments to collect data and model decision-making processes in AV–VRU interactions. Conduct real-world testing
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will also work in close collaboration with a partner group specialized in 2D materials (Goswami group) and a theory group (Wimmer group) for numerical simulations. We welcome applications from motivated
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skills in one or more scientific computing environments, such as Python, MATLAB, or similar. Experience with numerical modelling and simulation, preferably using finite element (FE) and/or multibody
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, will be employed to identify indicators of track and bridge condition. In parallel, physics-based numerical models will be developed to simulate train–track–bridge dynamic interactions and their
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modelling is an advantage. Strong quantitative skills and interest in statistical modelling, or simulation approaches. Experience with R, STATA, Python or similar software. Ability to work independently and
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degree in a STEM field. You love physics and complex systems and are either familiar with, or very eager to learn about, (road) network traffic flow theory and simulation. You are a machine learning
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of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after
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processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We
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, enabling breakthroughs such as memory-enhanced quantum communication, entanglement-based quantum networks, long-term quantum information storage, and complex quantum simulations. While these demonstrations
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networks, long-term quantum information storage, and complex quantum simulations. While these demonstrations point to a wide range of applications, critical challenges regarding color center physics and