Research & Development

Postdoctoral Fellow / Research Associate - Transfer learning for adaptive diagnostics and simulation-based analysis

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 a systematic methodology for effective fault diagnosis and/or predictive maintenance. It is expected that the projects will focus on applications in transportation or power utilities maintenance.
The Postdoctoral Fellow appointee will be required to:
conduct studies of related literature and applied research;
design and implement AI and data analytical techniques to address reliability and safety issues;
supervise junior researchers to conduct studies of related literature and applied research;
report research progress and results regularly to project team;
write and publish articles in high-tier peer-reviewed journals; and
perform any other duties as assigned by the Centre Director or his delegates.
The Research Associate appointee will be required to:
conduct studies of related literature and applied research;
design and implement AI and data analytical techniques to address reliability and safety issues;
report research progress and results regularly to project team;
support writing and publishing articles in high-tier peer-reviewed journals; and
perform any other duties as assigned by the Centre Director or his delegates.

Applicants for the post of Postdoctoral Fellow should have a doctoral degree in Computer Science, Engineering, Mathematics or an equivalent qualification in a related field. They should also have strong analytical skills with interests in big data and artificial intelligence.
Applicants for the post of Research Associate should have a master’s degree in Computing Science, Engineering, Mathematics or a related field.
For both posts, applicants should also have:
proficiency in programming language (e.g. C, Python, Matlab);
good interpersonal and communication skills; and
good command of written and spoken English.
Fresh graduates are also welcome.
Preference will be given to those with research experience in machine learning and data science.

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