公司簡介
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 in the School of Nursing and Health Sciences:
Research Associate/Postdoc (N&HS) (Ref: 26001HQ)
Major Duties and Responsibilities
The team is seeking a highly motivated and talented Research Associate/Postdoc, working with Prof. Agnes Lai. The successful candidate will assist Principal Investigators and support the research project related to statistics in health and social sciences contexts.
The appointee will be responsible mainly for the following:
- Performing statistical methods and quantitative research to address questions in health and social sciences (including health outcomes, health behaviors, health services, and related study design);
- conducting literature review on relevant topics;
- performing data analysis;
- drafting manuscript for publications (at least 2 publications are expected);
- supervising research students;
- reporting research progress regularly; and
- providing research-related assistance.
Candidates
Candidates should possess the following qualifications, experience, and competence:
- a recognized PhD degree (within 3 years of graduation), preferably in statistics, biostatistics, public health, nursing research, epidemiology, health policy, health/social science method, or related disciplines;
- demonstrated expertise in statistics and experience applying statistical techniques to health or social science research;
- a strong publication record, with at least one first-author paper published or accepted in a reputable, peer-reviewed journal related to the health and social sciences area;
- experience with quantitative or health research methods such as regression modelling, causal inference/observational analysis, longitudinal methods, survey methods, or other similar methods will be an advantage;
- a strong command of written and spoken English and Chinese;
- a good team player, and also able to work independently; and,
- a strong sense of self-motivation and responsibility, intellectual curiosity, critical thinking skills, and the ability to design and execute research independently.
Duration
2 years
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.
https://hkmu.taleo.net/careersection/ex_full_time/jobapply.ftl?lang=en&job= 26001HQ
Closing date of application: 30 Sep 2026
