[visionlist] PhD position in deep learning for computer vision (few-shot incremental learning)

[Jose Dolz]

Applications are invited for one fully funded PhD position at the ETS
(École de Technologie Supérieure), 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
summer 2024). Financial support is available for 4 years. In particular,
this project will focus on novel learning strategies that can accommodate
novel tasks/scenarios (unseen classes, domain shifts, etc) with only a few
labeled samples, without forgetting the knowledge already learned. Other
problems, such as generalized class discovery or class unlearning may be
explored too. The successful candidate will work under the supervision of
Prof. Jose Dolz and collaborate closely with an industry partner (to be
disclosed to selected candidates) .

   - Prospective applicants should have:
   - Strong academic record with an excellent M.Sc. degree (or equivalent)
      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 (preferably PyTorch).
      - Research experience in computer vision, machine learning or image
      processing is also desirable.
      - Publications in a peer-reviewed journal or conference in a related
      topic is a bonus.
      - For consideration, please send a full CV, 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
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