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Employer Ref: 24002SL
Recruit Ref: L059206118
Posting Date: 2025-01-10
Hong Kong Metropolitan University
Hong Kong Metropolitan University

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.

Part-time Research Assistant II (R6758 & R6759) (S&T) (Ref: 24002SL)

We are now looking for a suitable person to fill the following position in the School of Science and Technology:

Part-time Research Assistant II (R6758 & R6759) (S&T) (Ref: 24002SL)

 

Major Duties and Responsibilities

The appointee will mainly assist the research team in the research projects “Application of Artificial Intelligence (AI) Techniques in Forecasting the Variation of Sediments in Water Ecosystem” (R6758) and "Application of AI-enabled Prediction of Riverine Ecosystem Health for Sustainable Development" (R6759) He / She will be responsible mainly for the following:

  • Performing data analysis;
  • Assisting in report writing and presentation of the results;
  • Providing effective research and teaching-related assistance; and
  • Carrying out other research activities as instructed by the Investigators.

 

Candidates

Candidates should possess the following qualifications, experience and competence: 

  • A Bachelor’s degree or above in Hydrology Engineering, Civil Engineering, Computer Engineering, Computer Science or a related discipline;
  • Demonstrated proficiency in literature acquisition, English literature reading and critical thinking skills;
  • Basic programming skills in applying machine learning (Python, Matlab etc.) in the field of engineering, with a keen interest in applying AI into engineering applications are preferred;
  • Experience in preparing manuscripts for top-tier journals/conferences is preferred; and 
  • Knowledge of sediment dynamics, especially in multi-scale investigations will be an advantage.

 

Terms and Conditions for Appointment

Successful candidate will be appointed on a temporary part-time contract. Benefits will be provided in accordance with the statutory provisions.

 

To Apply

Candidates who are interested in joining us may submit their applications via the University’s eRecruitment System. 

https://hkmu.taleo.net/careersection/ex_non_full_time/jobapply.ftl?lang=en&job=24002SL

Closing date of application: 26 January 2025

 

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.


Summary
Industry:
Education / Training 
Job Category / Function:
Job Position Level:
General 
Employment Term:
Part Time 
Min. Edu. Level Req:
Bachelor 
Minimum QF Level attained:
-- 
Total Working Exp:
-- 
Salary(HKD):
--
Location:
Kowloon City District / Kowloon City
Benefits:
--
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