(1)     Postdoctoral Fellow

(2)     Research Associate

 [Appointment period: thirty-six months]

Duties (Ref: P3.3 - Forecasting maintenance)

The appointees will report to the Project Leader and the Centre Director or his designate (currently Program 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 (R11/P3.3) appointee will be required to:

a) conduct AI research to address industrial reliability and safety issue of product, process, and system.
b) conceptualize, plan and conduct research activities to achieve project deliverables.
c) develop innovative methodology based on sensors, machine/deep learning models for industrial application.
d) work with team of researchers and lead junior researchers to conduct research, experiment, and report;
e) perform any other duties as assigned by the Centre Director or his delegates.

The Research Associate (R12/P3.3) appointee will be required to:

a) conduct AI research to address industrial reliability and safety issue of product, process, and system.
b) develop innovative methodology based on sensors, machine/deep learning models for industrial application.
c) conduct research, experiments, and report/paper publications.
d) perform any other duties as assigned by the Centre Director or his delegates.

Duties (Ref: P4.1 - Functional safety improvement through expanded diagnostic coverage and reduction in testing effort)

The appointees will report to the Project Leader and the Centre Director or his designate (currently Program Manager), and perform research and related work in using deep learning methods for products in production to identify probable failure modes in advance based on physics of failure.

The Postdoctoral Fellow (R13/P4.1) appointee will be required to:
a) conduct studies of international standards, publications, and patents to support the design and implementation of project.
b) conceptualize, plan and conduct research activities to achieve project deliverables.
c) develop innovative methodology based on sensors, including machine/deep learning models for industrial application.
d) work with team of researchers to conduct research, experiments, and report;
e) write and publish articles in high-tier peer-reviewed journals; and
(f) perform any other duties as assigned by the Centre Director or his delegates.

The Research Associate (R14/P4.1) appointee will be required to:
a) conduct research to address industrial reliability and safety issue of product, process and system.
b) develop innovative methodology based on sensors, including machine/deep learning models for industrial application.
c) conduct research, experiments, and report/paper publications as assigned by Centre director or his delegates.
d) perform any other duties as assigned by the Centre Director or his delegates.

Qualifications (Ref: P3.3 - Forecasting maintenance)

(a) Postdoctoral Fellow (R11/P3.3): 
Doctoral degree holder in Computer Science, Electronic/Electrical Engineering, Information Engineering, Mechanical Engineering, Material Science, Physics, Mathematics, or relevant disciplines.

(b) Research Associate (R12/P3.3):
Master degree holder in Computer Science, Electronic/Electrical Engineering, Information Engineering, Mechanical Engineering, Material Science, Physics, Mathematics, or relevant disciplines.

(c) Professional background or experience with least one of the following areas:

1) Machine-learning/ data sciences related project
2) Software: Python, Labview, Matlab, etc. Familiar with open-source libraries including Tensorflow is a plus
3) Familiar with motor design and testing
4) Modelling and simulation
5) Product reliability

Qualifications (Ref: P4.1 - Functional safety improvement through expanded diagnostic coverage and reduction in testing efffort)

Postdoctoral Fellow (R13/P4.1)
Doctoral degree holder in Computer Science, Information Engineering, Mechanical Engineering, Material Science, Physics, Mathematics, or relevant disciplines. 

Research Associate (R14/P4.1)
Master degree holder in Computer Science, Information Engineering, Mechanical Engineering, Material Science, Physics, Mathematics, or relevant disciplines. 

(c) Professional background or experience with high competency in least one of the following areas:

1) Machine-learning/ data sciences related project.
2) Software: Python, familiarity with open-source libraries including Tensorflow is a plus.
3) Mechanical design and testing
4) Modelling and simulation
5) Product reliability
6) Material analysis

(e) Good command of written and spoken English

Remuneration
A highly competitive remuneration package will be offered. Applicants should state their current an expected salary in the application.

Application

1) Please download our job application form from "https://www.cairs.hk/assets/files/Careers/Job_Application_Form.pdf" 

2) Please return the completed application form, together with a detailed curriculum vitae, to the CAiRS by email to us or clicking "apply now"

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

Centre for Advances in Reliability and Safety Limited (CAiRS), initiated by The Hong Kong Polytechnic University, is a research centre admitted under [email protected] cluster and is established in 2020 with its operation located in the Hong Kong Science Park, New Territories, Hong Kong. The mission of CAiRS is to bridge academic and industrial counterparts to introduce and implement artificial intelligence methods and prognostic techniques to advance reliability and safety. The goal of the Centre is to improve reliability and safety of critical components and devices, products, systems and sub-systems designed, commissioned and/or manufactured by Hong Kong companies and enterprises. More information about the company can be found at http://www.cairs.hk.