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of the PhD topic (subproject A7- Reinforcement learning for mode choice decisions): This PhD project will develop and implement a Deep Reinforcement Learning (DRL) model for dynamic mode choice within
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with reducing and oxidising gas-phase species (e.g. laser-based imaging diagnostics, setup of model reactors, modelling of underlying reactions, multi-scale simulation of reactive fluids, computational
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analysis of mobility behavior, the application of agent-based models and road space analysis, particularly for road safety. Research on walking and cycling as a cross-cutting issue has a high priority in all
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develop data-inspired and data-driven models of sarcomere assembly. This will involve mean-field models and agent-based simulations. Additionally, depending on your aptitude, you can analyze topological