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Postdoctoral position in Hardware Acceleration for Deep Learning, University of Guelph

Country/Region : Canada

Website : http://www.uoguelph.ca

Description

The Machine Learning Research Group at the university of Guelph has a fully-funded 1 year postdoctoral position in the area of FPGA-based Hardware Acceleration for Deep Learning. The position will start on May 1, 2015. The postdoc will work closely with Dr. Graham Taylor and Dr. Shawki Areibi and their respective research teams. The project involves developing new representation learning and deep learning architectures and algorithms with a focus on reducing the amount of training time to discover optimal models.
The position is sponsored by a major international industry partner and will require occasional travel to Toronto (e.g. one day every two weeks). Company scientists and engineers are actively engaged in the project. The team aims to publish the results of the research, with the candidate taking a lead role in publication.
Ideal candidates will have a PhD in Computer Engineering, Computer Science, Physics, Mathematics, or in a related area, and have a strong interest and experience in hardware acceleration (specifically FPGA-based computing), machine learning, statistics and/or scientific computing evidenced by a strong publication record in top-tier conferences and journals. We will consider candidates whose primary research area is Machine Learning or Hardware Acceleration. Preference will be given to candidates who have exposure to both areas. Experience with deep learning frameworks, e.g. Caffe, Torch, Theano and FPGA software tools, e.g. OpenCL, Vivado HLS is an asset.
Teaching is not a requirement of the position, but the candidate is expected to supervise and mentor graduate and undergraduate students in a research capacity.
Guelph is a vibrant university community 28 kilometres east of Waterloo and 100 kilometres west of downtown Toronto, with commuter train access to both. It is consistently rated as one of Canada’s best places to live.
The Machine Learning Research Group at the University of Guelph consists of approximately 15 students, postdocs, researchers and visitors. The group focuses on deep learning and biologically-inspired computer vision. The group holds two compute clusters (250 TFLOPS peak performance), which are among the best GPU-based computing resources in Canada: a 10-node, 30 GPU cluster of Nvidia Titan Black cards, and an 8-node, 64 GPU cluster of Nvidia K80’s connected by Infiniband. The group is currently engaged in several projects at the intersection of deep learning and high performance computing.
The position is open to Canadian and foreign candidates. The salary is $60,000 CAD per annum plus benefits. To apply, please send the following documents in a single pdf-file to Dr. Taylor:
(1) Your Curriculum Vitae
(2) A brief statement of relevant research interests and/or experience (preferably one page, at most two)
(3) Transcripts for previous degrees if available
(4) Names of two or three referees who are able to comment on the applicant's qualifications. We will contact references of short-listed candidates only.
We will start reviewing applications on February 15 and will continue until a successful candidate is found. Only short-listed candidates will be contacted.

Last modified: 2016-02-07 15:00:51