Postdoctoral Fellow / Research Associate (AI, Machine Learning, Ensemble...

Postdoctoral Fellow (Ref. No. CAiRS-R7-R8/P2.2 - Machine Learning/ Ensemble methods for individualized fault diagnosis)
[Appointment period will end on 30 June 2025]

Research Associate (Ref. No. CAiRS-R7-R8/P2.2 - Machine Learning/ Ensemble methods for individualized fault diagnosis)
[Appointment period will end on 30 June 2025]

Duties

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 the transportation industry.

The Postdoctoral Fellow appointee will be required to:

1. conduct studies of related literature and applied research;
2. design and implement AI and data analytical techniques to address reliability and safety issues;
3. supervise junior researchers to conduct studies of related literature and applied research;
4. report research progress and results regularly to project team;
5. write and publish articles in high-tier peer-reviewed journals; and
6. perform any other duties as assigned by the Centre Director or his delegates.

The Research Associate appointee will be required to:

1. conduct studies of related literature and applied research;
2. design and implement AI and data analytical techniques to address reliability and safety issues;
3. report research progress and results regularly to project team;
4. support writing and publishing articles in high-tier peer-reviewed journals; and
5. perform any other duties as assigned by the Centre Director or his delegates.

Qualifications

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:

1. proficiency in a programming language (e.g. C, Python, Matlab);
2. good interpersonal and communication skills; and
3. 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.

 Salary:

• The maximum monthly salary allowance is HK$23,000 for research talents with a master degree and HK$35,000 for those with a doctoral degree.
• An additional monthly living allowance of HK$10,000 will be provided to research talents with a doctoral degree.

What you enjoy at CAiRS:

We offer highly competitive salary commensurate with qualifications and experience, in addition to the following benefits:

• 5-day work
• Staff's entitlement to paid annual leave will increase progressively according to the Centre’s guideline
• Flexible working hours (for researchers)
• Medical & dental insurance
• Excellent and friendly office environment (newly renovated and next to seashore)
• Work-life balance
• Free drinks and snacks in office

What you enjoy at Science Park:

• Shuttle bus to Science Park from various locations in HK
• Recreational facilities in Science Park, e.g. gym and swimming pool
• Can apply for studio apartment in InnoCell [link removed] (a smart living and co-creation space designed for I&T talents in Science Park) subject to availability and eligibility

Application Guidelines

1. Please return the completed application form, together with a detailed curriculum vitae, to the CAiRS via 
2. Application form can be downloaded from here [link removed]
3. Applicants who are not invited to an interview within two months of the closing date should consider their applications unsuccessful

The information provided will be treated in strict confidence and be used only for consideration of your application for relevant / similar posts within the Group/ Company.