|Title: Deep Learning Architectures for Recognition in Video Surveillance||Posted: May 4, 2017|
|Company/Institution: École de technologie supérieure, Université du Québec|
|Location: Montreal, Canada|
Description: Applications are invited for a funded Ph.D. position in machine learning at the École de technologie supérieure (ETS), U. of Quebec, Montreal, Canada. The candidate will work under the supervision of Prof. Eric Granger in the Laboratory for Imaging, Vision and Artificial Intelligence (LIVIA, see link below). The position is available immediately after the candidate passes ETS application requirements. Financial support is available for the project’s duration (maximum of 3-4 years).
We are looking for highly motivated doctoral students, who are interested in performing cutting-edge research in spatiotemporal face recognition of actions and faces in video surveillance applications, with a particular focus on deep learning (e.g, CNN and LSTM) architectures, information fusion and domain adaptation.
Prospective applicants should have:
• Strong academic record with an excellent M.Sc. degree in computer science, applied mathematics, or electrical engineering, preferably with expertise in one or more of the following areas: machine learning, neural networks, computer vision and face recognition;
• A good mathematical background;
• Good programming skills in languages such as C, C++, Python and/or MATLAB.
A prior publication in one of the major conferences or journals in computer vision/machine learning is not necessary but would be a very desirable.
Application Instructions: For consideration, please send a resume, names and contact details of two references, transcripts for undergraduate and graduate studies, and a link to a Masters thesis (as well as relevant publications if any) to Prof. Eric Granger (Eric.Granger@etsmtl.ca)
Laboratory for Imaging, Vision and Artificial Intelligence (LIVIA):