CENTRE FOR ADVANCES IN RELIABILITY AND SAFETY LIMITED

Centre for Advances in Reliability and Safety Limited (CAiRS), initiated by The Hong Kong Polytechnic University, 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.

Data Scientist (Ref. No.: CAiRS-DS/P5.1)

Duties

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 research project – “Sharable knowledge database”.  The appointee will work on the industry-driven research projects and build demos and proofs of concepts for business data analytics. He/She will work in a team of research associates/engineers and postdoctoral researchers, and collaborate with our industry partners to help develop tailor-made, state-of-the-art solutions.

Qualifications

Applicants should:

1. have a recognized degree or above in Data Science, Computer Science, Electrical/Electronic/Mechanical/Mechatronics, Information Engineering, Mathematics, Statistics or System Engineering or relevant disciplines, preferably with a master’s degree or a doctoral degree in aforementioned disciplines;
2. have a good command of written and spoken English and Chinese, with proficiency in Putonghua being an advantage;
3. be familiar with data analysis, visualization, and machine learning algorithms, e.g. logistic regression, random forest, SVM, CNN/RNN/LSTM;
4. be familiar with SQL/database/big data systems, e.g. Hadoop, MySQL, SQLServer and Oracle, DB2;
5. have good knowledge of at least one of the deep learning frameworks, e.g. Tensorflow, PyTorch, Caffe, and MxNet;
6. have good knowledge of cloud computing and virtualization technologies, e.g., Azure, Amazon AWS and VMware ESXi;
7. have extensive experience in communicating with and presenting to customers and partner engineers;
8. be responsive, self-motivated and deadline-driven;
9. be a quick learner of state-of-the-art technology;
10. have integrity on research activities and results; and
11. perform any other duties as assigned by the Centre Director or his delegates.

Applicants are invited to contact Dr Haibo Hu at tel no. 3400 3557or email haibo.hu@polyu.edu.hk for further information.

What you enjoy at CAiRS:

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

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

Application Guidelines

1. Please return the completed application form, together with a detailed curriculum vitae, to the CAiRS by email to careers@cairs.hk 
2. Application form can be downloaded from here.
3. The CAiRS reserves the right to fill or not to fill the position. The personal data in relation to your application will be used by CAiRS to assess your suitability for assuming the position you are applying for, and to determine the remuneration and benefits package, if applicable.
4. Please read the “Personal Information Collection Statement for Recruitment” before completing the application form.
5. The CAiRS is an equal opportunity employer committed to diversity and inclusivity. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, nationality, family status or physical or mental disabilities.
6. Applicants who are not invited to an interview within two months of the closing date should consider their applications unsuccessful.