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or mechanical engineering well above average and you should have experience in agent-based modelling and simulation. Fundamental knowledge of the key disciplines in aerospace engineering and especially in airport
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-assisted scenario generation for safety validation, data-driven test scenario selection using measured sim2real gap, and replicable evaluation based on provenance models (Positions #11, #12, #14, #15
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and/or AI-based approaches), including the integration of concepts such as reinforcement learning and multi-agent reinforcement learning Further development and use of virtual test environments
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. Research Focus The rise of powerful Large Language Models (LLMs) and autonomous AI agents is set to fundamentally change the practice of software engineering. As AI evolves from simple co-pilots to agents
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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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and verifiably safe. We consider resilience and intelligence to be part of the same process. What you will do Advancements in agent-based AI approaches are gaining significant attention in industry due
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research and teaching in Service Engineering. Her research aims to build models for understanding the impact of customer and agent behavior on service systems and to incorporate these behaviors
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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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ideas and immerse yourself in innovative research fields, including: Traffic optimization using multi-agent Reinforcement Learning and hierarchical Reinforcement Learning Reinforcement Learning-based
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No Description/content The Regenerative Sciences PhD programme (PhD RegSci) at the MHH (Hannover Medical School) focuses on novel regenerative agents and biomaterials as well as cell transplants