PhD position in designing novel memristive-based few-shot learning neuromorphic chips
We are looking for outstanding PhD students to design the next generation of memristive based few-shot learning neuromorphic chips. The project is within the recently-funded SNSF Starting Grant project UNITE: Brain-inspired device-circuits-algorithm co-design for resource-constrained hardware on the edge (https://www.ini.uzh.ch/en/public/news?id=101592).
In the project, the students will take advantage of the temporal and spatial sparsity principles of the brain to design power and memory efficient intelligent edge systems.
What we offer
The candidate will earn a PhD degree in one of the world-leading hubs for neuromorphic engineering, interacting with a diverse group of scientists ranging from neuroscience to computational modeling and Neuromorphic engineering. Salary is according to the guidelines of the Swiss National Science Foundation. We take diversity and gender equality very seriously.
The PhD candidate should have a Master’s degree in Electrical/Computer Engineering, with a strong background in analog circuit design, and preferably have knowledge on AI hardware. Specifically, the candidate should have taken classes in VLSI design, have systems knowledge, and performed analog or digital ASIC design in a prior project. The PhD candidate is also expected to be passionate and curious about the workings of the brain.
The ideal applicant would have experience in one or possibly more of these areas:
* Cadence IC design tools
* Analog circuit design
* Asynchronous digital circuit design
* Resistive memory devices and technologies
Interested applicants should send a statement of interest, CV, and transcripts to melika (at) ini.uzh.ch with subject line “Application for memristor-based on-chip-learning design”. Deadline for application is January 31st or until the position is filled.