Research Assistant I/II (R6965) (S&T) at Open University of Hong Kong

, Hong Kong, China -

Full Time

Start Date

Immediate

Expiry Date

13 Aug, 26

Salary

0.0

Posted On

15 May, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Literature Review, Data Collection, Data Annotation, Data Pre-processing, Machine Learning, Frontend Frameworks, Backend Technologies, API Development, Full-stack Development, English Proficiency, Chinese Proficiency, Interpersonal Skills, Organizational Skills

Industry

Higher Education

Description

Founded in 1989, Hong Kong Metropolitan University (HKMU) is a modern, vibrant and dynamic university. We tailor our professional programmes to adapt to market trends and meet industry needs, thus providing our students with quality professional education and clear career paths. Being the first University of Applied Sciences (UAS) in Hong Kong, we pledge to play a pioneering role in enhancing recognition of vocational and professional education and training, and nurturing talents with both applied skills and knowledge. As a faculty-driven, student-centred university in support of innovative teaching and learning, strategic research, and stakeholder outreach to provide maximum benefit to our communities, we conduct research that advances knowledge and enhances teaching, focusing on strategic areas, including digital humanities and literature, international business, gerontechnology, personalised care, smart city, open and innovative education, and bilingual learning and teaching. HKMU is becoming an ever more vital link in addressing and helping Hong Kong to solve many difficult challenges – as part of our involvement in, and commitment to, the ‘metropolis’ of Hong Kong. Our plans to expand into the Greater Bay Area (GBA) will also cultivate talent to serve Hong Kong and the wider metropolitan GBA. For more information about the University, please visit https://www.hkmu.edu.hk. We are now looking for a suitable person to fill the following position(s) in the School of Science and Technology: Major Duties and Responsibilities The appointee(s) will mainly assist the project team in a research project “Driving Performance Analysis Assistance System for Driving Tests” (R6965). The appointee(s) will be responsible mainly for the following: Conducting literature review; Collecting data; Assisting in data annotation; Carrying out data pre-processing and post-processing; Designing and developing machine learning models; Performing analysis on machine learning models; Collaborating with the engineering team to implement user interfaces using modern frontend frameworks; Collaborating with the engineering team to develop server-side logic and APIs using backend technologies; Assisting in documentation; and Carrying out other research activities as instructed by the project team. Candidates Candidates should possess the following qualifications, experience and competence: A master’s degree or above in Electronic Engineering, Computer Engineering, Computer Science, Data Science, Artificial Intelligence, Software Engineering, Information Engineering or a related discipline (for Research Assistant I); A bachelor’s degree or above in any of the above-mentioned disciplines (for Research Assistant II); Possessing industry experience, particularly full-stack developer experience, will be an advantage; Holding a valid Hong Kong driving licence will be an advantage; Good command of English and Chinese; Good interpersonal and organizational skills; and Able to communicate and work effectively in a diverse team. Please indicate in your CV the position that you wish to be considered for. Terms and Conditions for Appointment An attractive remuneration package, including basic salary and an end-of-contract gratuity will be offered to the right candidates. Generous annual leave, staff-development sponsorships, medical and dental benefits, and life insurance coverage will also be provided. To Apply Candidates who are interested in joining us may submit their applications via the University's eRecruitment System. (Applicants who have responded to the previous advertisement posted in April 2026 need not re-apply.) The personal data collected will be used for the purpose of considering your application for employment. For details, please refer to the “Personal Data (Privacy) Notice for Job Applicant” on the University’s website. If you are not contacted by the University within eight weeks from the closing date of application, you may assume that your application was unsuccessful.

Responsibilities

The appointee will assist in a research project focused on a driving performance analysis assistance system. Responsibilities include developing machine learning models, handling data processing, and collaborating with engineering teams on frontend and backend implementation.