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atomistic simulations, high-performance computing, and the application of AI-based methods Basic knowledge in photovoltaics and solid-state materials for energy application Ability to work individually and in
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the MATSim agent-based transport simulation framework. The main task is to enable simulated agents to choose transportation modes, such as car, bus, bike, or walking, based on real-time feedback from
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simulate, and eventually manipulate wave propagation under realistic scenarios by intertwining analysis and numerics. The proposed doctoral project concerns the mathematical analysis of dispersive phenomena
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: Prof. Dr. Steven Travis Waller, Chair of Transport modeling and simulation, and co-supervised by at least one additional professor, plus an international tutor of the CRC Requirements: excellent
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Some experience with numerical simulations such as the Finite Element Method (FEM) and Multi-Body Simulation (MBS) is a plus. We offer: a fascinating understanding at mobility in general with a
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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of computer simulations to refine the targeted synthesis even more and predict the self-assembly even better. Who we are The Research Training Group RTG2670 – Beyond Amphiphilicity in the second funding phase
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trajectory, and performance evaluation in traffic simulation. Tasks: Independent and cooperative qualification through scientific research within the project; training in the technical tasks of the individual
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on mesoscale fluid dynamic simulations, microclimatic and turbulence modelling procedures in urban environments shall be performed. Subsequently weather-and turbulence-related limit values shall be formulated