Postdoc position in neuro/AI in the Zylberberg and Fyshe Labs

Hi All,

We seek exceptional candidates for a post-doctoral appointment to be held jointly in the Fyshe research group at the University of Alberta in Edmonton, and the Zylberberg research group at York University in Toronto. The appointment can be taken up at either institution, and will initially be for a one-year term and will be renewable for an additional year subject to satisfactory performance. The post-doctoral appointee will work with Alona Fyshe and Joel Zylberberg on activities related to using brain activity data as a “teacher” signal to help train artificial neural networks. Initial projects will include computer vision tasks such as object recognition and/or image captioning, but could extend to game play or natural language depending on candidate expertise. This project is funded by a New Frontiers in Research grant held jointly by Fyshe and Zylberberg.

Research will include:

• Deep learning, including training large models using GPUs
• Analysis of neuro-imaging data (e.g., fMRI, MEG or EEG).

Candidates must have demonstrated expertise in machine learning and training deep learning models. Backgrounds in cognitive science, neuroscience, and brain imaging, among others, are advantageous. We are especially interested in exceptional candidates who transcend traditional disciplinary boundaries and complement our existing strengths.

Please submit a cover letter, CV, one-page research statement, and 2-5 references to mmarvin+afjzpostdoc@ualberta.ca. We are looking for someone to start as soon as possible. The review of applications will begin on July 20 and will continue until a suitable candidate is found; in order to ensure full consideration, applications must be completed by July 30.

We are committed to an equitable, diverse, and an inclusive workforce.

University of Alberta

The Department of Computing Science (http://www.cs.ualberta.ca) is home to nearly 50 tenured and tenure-track faculty members and over 200 graduate students in its PhD and thesis-based MSc programs.

The University of Alberta (http://www.ualberta.ca) ranks consistently within Canada’s five best medical/doctoral universities. Over 31,000 undergraduate students, 7,600 graduate students, and 600 postdoctoral fellows are part of the university’s exceptional learning and research environment. Edmonton (http://www.edmonton.ca), Alberta’s capital, offers a rich array of cultural, professional, sports, and entrepreneurial activities, with easy access to Canada’s Rocky Mountains, and its public elementary and secondary schools provide high-quality education.

Edmonton is also home to the Alberta Machine Intelligence Institute (amii), which is part of the CIFAR $125M Pan-Canadian AI Strategy. Amii has attracted an extremely strong cohort of professors, post-docs and graduate students, and enhanced what was already a very strong machine learning community in Edmonton. Successful candidates will become members of amii, and will be able to take advantage of amii events and resources.

York University:

The Zylberberg research group is part of Vision: Science to Applications (VISTA) at York University. This is a collaborative program funded by the Canada First Research Excellence Fund (CFREF) that builds on York’s world-leading interdisciplinary expertise in biological and computer vision. VISTA is supported by over $100M in funding, from CFREF, York University, and other sources. In collaboration with over 50 academic, public, and for-profit partners from around the world, VISTA aims to propel Canada as a global leader in the vision sciences by integrating visual neuroscience with computer vision to drive innovation. VISTA has 33 core faculty members, and many master’s students, Ph.D. students, and postdoctoral fellows.

York University is located in Toronto, which is home to York, the University of Toronto, Ryerson University, and the Vector Institute for AI; the Vector Institute is part of the CIFAR $125M Pan- Canadian AI Strategy. Between these institutions, there is an extremely strong local community of both academic and industry researchers in machine learning.

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