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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 verification and formal
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Embedded AI, Edge AI, TinyML, and AIoT, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system
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that also act as green energy producers driving the societal transition towards net zero. In this position, you will build on your expertise in IoT and low-power computer and communication systems to research
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Electrophysiological signal processing of, e.g., EEG, ECG, EMG, etc. Health data science, incl. modern machine, and deep learning methods, Cloud-based platforms like MS Azure or Google Colab Health data standards, like
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and proposal preparation. Required qualifications: As a formal qualification, you must hold a PhD degree (or equivalent) in computer science, computer engineering, networking, or related fields relevant
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the development of context-aware, distributed, and embedded cyber-physical systems, with a particular focus on Internet-of-Things (IoT) and the computing continuum eras. Our vision is to pioneer advancements in