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. Responsibilities: Conduct research in time-predictable computer architecture. Designing a network-on-chip for real-time automotive systems Verify the design with modern verification methods, such as function
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learning approaches and develop a theoretical understanding potentially based on differential geometry. In particular, deep neural networks perform surprisingly well on unseen data, a phenomenon known as
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of Civil and Mechanical Engineering, Thermal Energy Section. We look for a talented, self-motivated, and team-oriented individual who thrives in a collaborative environment and enjoys tackling complex topics
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. Opportunities to participate in conferences, symposia, and networking events to share and enhance your research. Your role will be pivotal in driving AI innovation and contributing to a transformative approach to
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(a) networked multi-agent human-robotic systems that work collaboratively in a well-coordinated and safe manner, (b) computational design and digital manufacturing of components, (c) design of
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interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and