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Data Processing with Spiking Neural Networks for Electronic Skin Applications
Data Processing with Spiking Neural Networks for Electronic Skin Applications
Overview : A PhD project focusing on data processing with Spiking Neural Networks (SNNs) is available at Electrical Engineering Department at Uppsala University (UU). The position offers the opportunity to develop yourself in an emerging area of machine learning research as well as gain industry relevant skills. The project is a collaboration between researchers from Electrical Engineering Department at UU and Ericsson Research. The position is offered as a part of graduate school of Centre for Interdisciplinary Mathematics (CIM) at UU.
Background: Inspired by information transmission and processing in brain, spiking neural networks provide an attractive paradigm for event-driven computing. Together with implementation on neuromorphic hardware, SNNs exhibit promising features for fast, massive, event-driven, asynchronous data processing while reducing the energy cost. In the recent years, these benefits of SNNs have led to extensive research activity on SNNs by researchers from a large array of fields including neuroscience, machine learning, embedded system design and neuromorphic chip design.
Project Description: Despite many recent advances, there is still no well-established strategy for efficient training and learning with SNNs. This PhD position focuses on this gap. Electronic-skin applications, which have important use cases for prosthetics, virtual reality and robotics, is an important part of the project.
The main aims of the project are two fold:
to develop real-time, event-driven data processing methods using SNNs
to customize the developed solutions for e-skin applications.
In addition to working with researchers specializing in data processing and machine learning, the candidate will also have a chance to interact with researchers working on hardware for e-skin at UU as well as our collaborators in Ericsson Research, who are actively involved in projects focusing on hardware architectures for machine learning, SNNs and neuromorphic computing.
PhD Candidate: This project will allow the PhD candidate to gain knowledge/skills on an emerging research area in machine learning, i.e. spiking neural networks, as well as an interesting application area, i.e. electronic skin. Development of efficient learning solutions with SNNs is the primary aim of the project. Hence, the candidate is expected to develop the level of mathematical maturity to be able to advance the theory for SNNs and the programming skills necessary for implementations of SNNs.
The project details can be found at the link below:
If this project sounds interesting, please contact Ayca Ozcelikkale (a y c a [dot] ozcelikkale [ -?- ] angstrom [dot] uu [dot] se (-?- = -a-t-)) or André Teixeira (andre[dot] teixeira [ -?- ] angstrom [dot] uu [dot] se (-?- = -a-t-))
To apply for the PhD position, please use the following link: application (Last day for application is March 31.)
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