Temporary Research Associate / Assistant I/II / Technical Assistant (Project no: R6968) (B&A)
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 inviting suitable candidate(s) to join us in the Lee Shau Kee School of Business and Administration for the following post(s):
[For Research Project “Reconfiguring Supply Chains: Evidence from Case Studies” (Project No. R6968)]
Major Duties and Responsibilities
The appointee shall mainly be responsible for the following:
l Collecting data from the Internet;
l Conducting data analysis and compiling reports; and
l Providing assistance in other areas related to the research project.
Candidates
Candidates should possess the following qualifications, experience and competence:
l Preferably a recognized higher degree in computing or related area;
l Strong publication record;
l Good data analytics skills; and
l Experience in collecting information from Websites via a Web scrapping tool.
The candidate should be willing to learn new technologies and able to work independently. Knowledge in online learning is preferable but not essential.
To Apply
Candidates who are interested in joining us may submit their applications via the University’s eRecruitment System.
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. The University will continue to review applications until the position(s) is/are filled.
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