Open PhD positions in event-driven deep network algorithms and hardware accelerator for prosthesis stimulation
The
Sensors Group at the
Inst. of Neuroinformatics, UZH-ETH Zurich has
two open PhD (or one talented postdoc) positions for an upcoming multi-partner European-level project . The institute provides a multi-disciplinary research environment. The Sensors group focuses on bringing concepts together from machine learning, signal processing, and neural processing; and mapping the network architectures onto high energy-efficiency low-latency hardware accelerators and sensors.
This project will involve a multi-partner interdisciplinary team to develop a neuroprosthesis system whose details will be provided in a future update or through personal communication. The student in the first position will work on hardware-aware deep network algorithms to produce stimulation patterns from video. The student in the second position will map these algorithms onto a real-time high energy-efficiency hardware FPGA or ASIC platform. The students will work with the various partners on both the algorithm and the interfacing of the hardware to the stimulation platform.
Positions
Position 1: Event-driven deep network algorithms
Requirements: Strong background in machine learning, deep networks
Position 2: Hardware accelerator for deep networks
Requirements: Strong background in electrical engineering and experience with hardware including FPGA and/or real digital (and analog) IC design using Cadence/Mentor tools.
Contact
Deadline for application is September 2020 or until the position is filled.
Interested candidates should send email to Dr. Shih-Chii Liu (shihatini.uzh.ch) with subject line containing “Prosthesis position” and include the following material
- 1. Your email should summarize briefly your background, accomplishment, and particular interest in the project
- 2. Your CV including TOEFL, GRE, project/publication accomplishments, and 1 or 2 possible references.
- 3. Your grade transcripts from undergraduate and masters programs