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utilization. We conduct research in the field of sustainable bioeconomy, focusing on the development of innovative microbial production systems based on renewable raw materials. Our goal is to establish new bio
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RAICAM aims to train a cohort of 10 PhD students to work on the next generation of mobile robots for inspection and maintenance of industrial facilities. RAICAM will develop a multi-domain, multi-agent
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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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to reason about software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new
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to reason about software (e.g., LLM agents for finding and fixing bugs)Static and dynamic program analysis (e.g., to infer specifications)Test input generation (e.g., to compare the behavior of old and new
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. They work together to enhance our understanding of intelligence, cognition in autonomous agents, and teams of agents in the context of mediatised worlds. The insights are then transferred into a new
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single industrial environmental burden of our generation. Disruptive innovations are required for alternative reduction processes that convert mineral ores into metals without today’s carbon-based methods
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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 defects of smectic
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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