[visionlist] Deep Learning Architectures Face Recognition in Video Surveillance

Applications
are invited for a funded PhD position in machine learning at the
École de technologie supérieure (ETS), U. of Quebec, Montreal,
Canada. The
candidate will work under the supervision of Profs. Eric Granger and
Ismail Ben Ayed 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 spatio-temporal
face recognition for 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
process: 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

Eric
Granger (Eric.Granger@etsmtl.ca)

Ben
Ayed, Ismail (Ismail.BenAyed@etsmtl.ca)

Laboratory
for Imaging, Vision and Artificial Intelligence (LIVIA):

http://ift.tt/2ohfRhj

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