National University of Singapore, Computer Architecture Lab

Position ID:NUS-Computer Architecture Lab-EENA [#15615, 0006]
Position Title: Postdoc Energy-Efficient AI/Neuromorphic Hardware Accelerators
Position Type:Postdoctoral
Position Location:Singapore, Singapore [map]
Subject Areas: Computer Science and Electrical and Computer Engineering / Computer Systems/Architecture, Machine Learning (with an applied and methodological focus)
Computer Science / Machine Learning, Machine learning methodology and applications, Systems, Ubiquitous Computing
Electrical and Computer Engineering / Edge Computing, Internet of Things, Machine Learning, Machine Learning/Data Science, Systems
Electrical Engineering / computer engineering, Internet of Things
Computer Science and Electrical Engineering / Deep Learning, Machine Learning (more...)
Appl Deadline:none (posted 2019/11/28)
Position Description:    

*** the list date or deadline for this position has passed, and no new applications is accepted. ***

Postdoc Energy-Efficient AI/Neuromorphic Hardware Accelerators

The National University of Singapore invites applications for the position of Research Fellow (Postdoc) in the Department of Computer Science, School of Computing (SoC). SoC is strongly committed to research excellence in all its dimensions: Searching for fundamental results and insights in developing novel computational solutions to a wide range of applications, building large-scale experimental systems, developing theories and policies for effective management of information systems in organizations, and improving the well being of society.

Neuromorphic computing, a new, promising alternative to artificial neural networks (ANN), shows promise as a way for handling highly-energy efficient inference tasks, like image recognition. To enable AI for Edge Computing, efficient alternatives to current ANN designs are needed. In this project, researchers will be responsible for working closely with the Principal Investigators (PIs) on a multi-year project to investigate implementation trade-offs that span the neuromorphic architecture, ties between low-level VLSI techniques and the computer architecture, as well as hardware-software co-design strategies. The best candidates will have familiarity with traditional computer architecture techniques, and have experience in AI/NN design and hardware optimization.

Please email us if there are any questions about this position.

Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
National University of Singapore
School of Computing
Computing 1
13 Computing Drive
Singapore 117417

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