Postdoctoral Fellow / Research Associate (Forecasting Maintenance)

1. Postdoctoral Fellow (Ref. No.: CAiRS-R11/P3.3 - Forecasting maintenance)

[Appointment period will end on 30 June 2025]

2. Research Associate (Ref. No.: CAiRS- R12/P3.3 - Forecasting maintenance)

[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 AI-based prognostic techniques to assess the extent of degradation from normal condition and enable the condition monitoring and predictive maintenance actions for electrical systems/devices.

The Postdoctoral Fellow appointee will be required to:

• • conduct AI research to address industrial reliability and safety issue of product, process, and system;

• conceptualize, plan and conduct research activities to achieve project deliverables;

• • develop innovative methodology based on sensors, machine/deep learning models for industrial application;

• work with team of researchers and lead junior researchers to conduct research, experiment, and report;

• 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 AI research to address industrial reliability and safety issue of product, process, and system;

• • develop innovative methodology based on sensors, machine/deep learning models for industrial application;

• conduct research, experiments, and report/paper publications; and

• • perform any other duties as assigned by the Centre Director or his delegates.

Qualifications

• Postdoctoral Fellow: Doctoral degree holder in Computer Science, Electronic/Electrical Engineering, Information Engineering, Mechanical Engineering, Material Science, Physics, Mathematics, or relevant disciplines.

• Research Associate: Master’s degree holder in Computer Science, Electronic/Electrical Engineering, Information Engineering, Mechanical Engineering, Material Science, Physics, Mathematics, or relevant disciplines.

• Professional background or experience with at least one of the following areas:

• Machine-learning/ data sciences/ digital twin/ IoT technology related projects

• Software: Python, Labview, Matlab, COMSOL etc. Familiar with open-source libraries including Tensorflow is a plus

System/device reliability and safety, and Prognostic Health Management (PHM)

• Good team player with excellent analytical and communication skills

• Good command of written and spoken English

Fresh graduates are also welcome.

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 (a smart living and co-creation space designed for I&T talents in Science Park) subject to availability and eligibility

Application

Please send a completed application form, together with a detailed curriculum vitae via email to [our mailbox through Apply Now] Application form can be downloaded from here

Deadline for application: Recruitment will continue until the positions are filled.

All applications applied through our system will be delivered directly to the advertiser and privacy of personal data of the applicant will be ensured with security.