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. The system will include: A very compact, ultra-low-power analog front-end (AFE) to sense neural signals. An on-chip neuromorphic processor to convert the neural data into spike-based encoded data and
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you will design, build and operate advanced electrochemical systems focused on product detection. The project builds upon many years of experience - for example with the "sniffer chip" which has been
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intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and
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specifically examine gas corrosion mechanisms in connection with copper and silver, while investigation also will be carried out on specific electronic components such as chip resistors, IGBT substrates etc
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intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and
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Neural Networks (SSM-SNNs). The project includes the co-design and integration of a RISC-V processor for hybrid neuromorphic computing. The research aims to develop ultra-low-power computing chips
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), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual
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. These are essential components for optical quantum computers and quantum networks, where one bit of information is encoded in the quantum state of a single photon. You will be part of a team of 10-12 people between
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in connection with copper and silver, while investigation also will be carried out on specific electronic components such as chip resistors, IGBT substrates etc. Work will also involve electrochemical