A Corp Lab in NTU is seeking to hire a Research Engineer II who will contribute to the development of graph-based reasoning networks for accurate and stable facial landmark detection models. The ideal candidate will possess the ability to apply recent technological advances in graph reasoning networks to the face alignment tasks.
Key Responsibilities:
- Develop graph-based reasoning networks for facial landmark detection.
- Develop spatial temporal graph-based reasoning network to improve the accuracy of video facial landmark detection.
- Develop stabilization methods for video facial landmark detection.
- Develop graph neural network theory.
- Develop sequence modeling theory.
- Develop deep learning methods and theory.
- Develop computer vision methods.
Job Requirements:
- Master's degree or higher in Computer Science/Engineering, or Electrical/Electronic Engineering.
- Strong mathematical background
- Top-tier AI venue publications are very much preferred
- Minimum of 2 years of work experience in a related field.
- 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.
