School of Computer Science and Engineering (SCSE) invites applications for the position of Research Associate.

Key Responsibilities:

• Development of graph-based reasoning networks for facial landmark detection.
• Development of spatial temporal graph-based reasoning network to improve the accuracy of video facial landmark detection.
• Development of stabilization methods for video facial landmark detection.
• Development of graph neural network theory.
• Development of sequence modeling theory.
• Development of deep learning methods and theory.
• Development of computer vision methods

Job Requirements:

• Master degree or above in Computer Science/Engineering, or Electrical/Electronic Engineering.
• Strong mathematical background and related project experience
• Top-tier AI venue publications are very much preferred
• Minimum 2 years of related work experience
• Deep understanding of the theory of Machine Learning, Deep Learning, Computer Vision
• Experience in at least one Deep Learning framework such as Tensorflow, Pytorch and Programming Languages such as Python, Matlab, R and/or C/C++
• Demonstrated project experience related to graph-based reasoning and facial landmark detection will be an advantage
• Good written and oral communication skills

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU