Research & Development

Postdoctoral Fellow (Computer Vision)

The appointees will report to the Project Leader and the Centre Director or his delegate (currently Programme Manager) and perform research and related work in the development of machine-learning-based anomaly detection algorithms and surveillance systems for health monitoring of modern electronic systems.
The appointee will be required to:
prepare literature review on machine vision methods on the anomaly detection of electronic assemblies;
design required machine vision systems as required in the health monitoring of modern electronic systems;
develop machine vision and learning algorithms for the anomaly detection and surveillance on the health of different components mounted on the electronic assemblies;
prepare and publish relevant research papers in high-tier peer-reviewed journals; and
perform any other duties as assigned by the Centre Director or his delegates.

Applicants should have a doctoral degree in Electrical/Electronic Engineering, or an equivalent qualification in a related field. They should have a good publication record.
For the post, applicants should also have/be:
Good understanding of computer vision, pattern recognition and machine learning.
Experience in algorithm development and implementation.
Proficient in programming languages including Python, C/C++.
Familiar with deep learning frameworks such as Tensorflow or Caffe.
Good interpersonal and communication skills; and a good command of written and spoken English.
Fresh graduates are also welcome.

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