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in research and development of sustainable energy conversion technologies. We are recognized as global leaders in this field, supported by state-of-the-art facilities and deep expertise. Our
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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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of biosignals features and processing techniques. Experience in designing Spiking Neural Networks (SNNs) or deep learning algorithms Preferably, experience with FPGA development of SNNs ASIC design experience is
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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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school with deep roots in the Nordic socio-economic model. Our faculty has a broad focus on societal challenges, and we have earned a reputation for high-quality disciplinary and interdisciplinary research