Research program title
Mixed-signal integrated-circuit design for neuromorphic computing
In this project, we explore the full range of digital and analog computational approaches to design ultra-low-power spiking neural network integrated circuits. The goal of this project is to move silicon systems one order of magnitude better in energy efficiency, when tasked with various AI benchmarks.
This is a team project with four Masters and PhD students. The successful applicant will make research contributions and mentor graduate students.
Glenn Cowan’s research group is active in wireline communication and mixed-signal design for avionic, biomedical, computational and communications applications.
Academic qualifications required
PhD in Electrical Engineering, with a track record of integrated-circuit (IC) design and testing. The ideal candidate has designed mixed-signal integrated circuits for machine-learning applications and has an interest in neural-network algorithms, however, IC design experience in mixed-signal or wireline communication will be considered.