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model complexes. This research is part of a large, funded collaborative project supported by the Swiss National Science Foundation, involving partner researchers based in Germany, Switzerland, and France
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Investigators: Dr.-Ing. habil. Judith Rosenow, Chair of Air Transport Technology and Logistics and co-supervised by at least one additional professor plus an international tutor of the RTG
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well as Mobility Modeling and Simulation. Research topics range from conceptual issues of strategic planning to small-scale analyses of specific street spaces. The chair’s methodological focus is on the empirical
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’ is therefore to investigate the influence of glucosinolate-based amines on the formation of Maillard-like products in model systems and foods, to isolate and identify the resulting products and to find
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: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry
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areas: software testing, runtime monitoring or diagnostics combined with a desire to embed these in today's assurance processes. Knowledge of software development methods (especially agile methods such as
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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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transformation." The project will investigate the relationship between road safety and safety culture. A theory-based model of road safety culture will be developed and validated through surveys in various
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calculation of mixture toxicity Development and application of chemical analytical methods Application of physiology-based kinetic (PBK) modelling for the extrapolation of in vitro to in vivo concentrations
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coating, iii) investigation of system design from small-scale to potentially pilot scale, and iv) application to micropollutant removal. Modelling aspects are open to exploration at molecular and process