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? We invite applications for a PhD position, focusing on the design and implementation of Spiking Neural Networks (SNNs) using CMOS technology. Project Overview This PhD position is part of a
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invite applications for an appointment as a PhD student in EEG Foundation Models. The position is funded by the Independent Research Fund Denmark grant titled: “Decoding neural signatures of social
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speech at the pinnacle of complexity. Like human babies, songbirds learn their vocalizations early in life from a social tutor. Numerous parallels to human speech learning, including analogous neural
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world-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and
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leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and
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analogous neural circuitry and shared molecular pathways have established songbirds as the model system of choice for human speech learning and fine motor control in general. The PhD candidate will use
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for brain signal acquisition Implementing an on-chip neuromorphic processor with a spike encoder and spiking neural network Developing a low-power spike-based transmitter. Setting up measurement systems and
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the Spiking Neural Network (SNN) itself. However, close collaboration with another PhD student working on the SNN hardware design is expected to ensure seamless signal interfacing and system integration. Key