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-computer interfaces, cognitive rehabilitation, and neural prosthetics. Your contributions will support the development of a custom CMOS-based SNN processor that can operate in ultra-low-power environments
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for intelligent brain-computer interfaces? We are offering a PhD position in analog/mixed-signal CMOS circuit design for EEG and wearable sensor interfaces, as part of a pioneering project focused on assistive
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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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Applicants should hold a relevant MSc degree in electronics, electrical engineering, computer engineering, or related fields. Required Qualification: Solid background in digital CMOS design and deep learning
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needed to achieve these temperatures, the control cables connecting to the qubits are often more than 2 meters long. At the same time, a quantum computer powerful enough to solve problems beyond the reach