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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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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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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will
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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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vision of creating world class knowledge in valuable collaboration with industry providing a unique opportunity to be part of the center. The center is collaborating closely with other Centre’s