Research Associate (JOB-2019-0165375)

​Job Description:

The research associate will be conducting research for a project on facial image processing and understanding, extending and pushing the frontiers on deep learning-based methods.

The potential topics that the researcher may be assigned to work on include:

  • accurate dynamic 3D reconstruction of facial shape, appearance and motion, 
  • inference of underlying personal attributes including but not limited to gender, age, emotions and moods, and; 
  • output image/video manipulation such as video-driven facial animation of avatars and caricatures, face relighting and facial attribute transfer between different individuals.

The research associate is expected to come up with independent research ideas, do extensive amounts of software coding on the latest research platforms, build and showcase research demo systems, conduct data collection and processing, and be able to independently write research papers. The individual should have high integrity, be self-motivated, independent and proactive, have matured reasoning and planning skills, and be able to work well in teams.

Job Requirements:

  • The candidate is expected to have good Masters degree in computer science or related discipline, with strong mathematical ability and programming skills in C/C++ and Python.
  • The candidate must be able to communicate well in English, with good presentation skills.
  • The candidate is expected to have previously worked with the latest deep learning platforms on projects in a related area.
  • Prior publications in related topics are not a requirement but will be preferred.


Application Procedure:

Interested applicants please attach your full CV (including educational background, research and work experience(s), list of publications and highlighting previous relevant experience), the names and contacts (including email addresses) of 3 character referees, and all relevant academic certificates to Assoc Prof Cham Tat Jen (

We regret that only shortlisted candidates will be notified.

Applications close when position is filled.

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