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Chair and Institute of Man-Machine Interaction | Aachen, Nordrhein Westfalen | Germany | 2 months ago
in applied artificial intelligence: in LLM-based assistance and agent systems, in knowledge provisioning, and in connecting language models with real tools and 3D simulation models. The focus is on
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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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Directions AI for Scientific Computing Neural Operators and Learning-Based Surrogates LLMs and Scientific Agents Agentic AI for Engineering Design Multimodal Scientific AI Alignment and Verification
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mobility services. Develop and estimate discrete choice models for transportation mode choice decisions. Implement and apply agent-based transport simulations to assess demand and modal-split changes under
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research focus may include the following areas: Fine-tuning of large language models on rewards derived from social interactions or collective outcomes Evolutionary adaptations of AI agents in social
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agent-based models to understand how RNAs and ribonucleoprotein (RNP) assemblies regulate gene expression, cellular behavior, and subcellular organization. Integration of transcriptomics, ribonomics
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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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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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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