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develops LLMs and agentic AI systems for scientific discovery, engineering and physical systems. We investigate how AI can reason about scientific problems, interact with simulation software and support the
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of LLM- and VLM-based methods for automotive software engineering Development of agentic AI systems with Human-in-the-Loop mechanisms for software development, testing, deployment, and maintenance Design
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mesoscopic properties of active units within a collective to its macroscopic behavior based on simulation data. Another possibility is to equip active units with learning capabilities or adaptive interactions
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project on transparent, agent-based AI methods to support multidisciplinary tumor boards in oncology. You will develop methods to transform heterogeneous oncology documentation into structured, time-aligned
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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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to characterize network-wide interventions, like reallocating road space or travel demand management schemes. Second, to develop an MFD-based traffic simulation linked to the agent-based simulation environment