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Postdoctoral position to develop a complete, ultra-low power brain-computer interface (BCI) for intuitive control of household appliances through EEG-based intention decoding. The project integrates stretchable EEG sensors, analog front-end, and embedded spiking neural networks (SNN) for real-time classification.
Job Responsibility:
Complete three work packages (WPs)
WP1: Development of Acquisition and Stretchable Electronic Module within first nine months
WP2: Development of Embedded SNN Module (ESM) before end of 18th month
WP3: Development of Decision Loop and Smart Appliance Control before end of project
Requirements:
Background in spiking neuronal network modeling
FPGA programming skills
Skills in general electronic circuit design
Knowledge of wet neuroscience, especially morphology and physiology of neuronal cells