[visionlist] PhD position in deep learning for computer vision
Jose Dolz
jose.dolz.upv at gmail.com
Sat Jun 6 22:27:38 -04 2020
Applications are invited for a fully funded PhD position at the ETS,
Montreal, Canada. ETS is the fastest-growing and largest engineering school
in Quebec, with an expanding team of highly qualified young researchers in
image analysis, computer vision and deep learning, some of the priority
areas of the school.
The position is available after the candidate passes ETS application
requirements and the candidate will start at her/his convenience (latest at
winter 2021). Financial support is available for 4 years. This project will
explore learning strategies for training when annotated data is limited
(e.g., few-shot segmentation, or unsupervisedly out-of-distribution
detection in dense prediction tasks, such as image segmentation). The
application domain could be either computer vision problems or medical
imaging applications (neuroimaging, oncology, etc). The successful
candidate will work under the supervision of Prof. Jose Dolz. Furthermore,
the selected student is expected to publish her/his research on top
computer vision and medical image analysis journals (IJCV, MedIA, IEEE TMI)
and conferences (CVPR, ECCV, ICCV, MICCAI, IPMI, etc).
Prospective applicants should have:
-
Strong academic record with an excellent M.Sc. degree in computer
science, applied mathematics, or electrical/biomedical engineering,
preferably with expertise in more than one of the following areas: medical
image analysis, machine learning, computer vision, pattern recognition,
semi/weakly supervised learning and/or optimization;
-
Experience with a deep learning framework (preferrably PyTorch, or
Tensorflow).
-
Knowledge of weakly or semi-supervised learning strategies.
-
Publications in a peer-reviewed journal or conference in a related topic
are a bonus.
For consideration, please send a CV, a cover letter, names and contact
details of two references, transcripts for graduate studies, and a link to
a M.Sc. thesis (as well as relevant publications if any) to:
jose.dolz at etsmtl.ca
--
*Jose Dolz*
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