Research Associate (Chronic Disease & Big Data) (N&HS) at Hong Kong Metropolitan University

, Hong Kong, China -

Full Time

Start Date

Immediate

Expiry Date

11 Feb, 26

Salary

0.0

Posted On

13 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Management, Statistical Analysis, Big Data, Bioinformatics, Literature Review, Grant Writing, Causal Inference, EHR, SQL, R, Python, Research Dissemination, Team Collaboration, Attention to Detail, Communication Skills, Problem Solving

Industry

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 in the School of Nursing and Health Sciences: Major Duties and Responsibilities The appointee will be an integral member of the research team in the School of Nursing and Health Sciences, primarily supporting research on chronic obstructive pulmonary disease (COPD), cardiovascular, and cerebrovascular diseases. The appointee will take ownership of data management, advanced statistical analysis, and the dissemination of research findings. The appointee will be responsible mainly for the following: Literature Review & Synthesis: Conduct comprehensive literature reviews to inform and support the development of research proposals and manuscripts in the fields of COPD, cardiovascular, and cerebrovascular diseases; Data Management & Curation: Build, manage, and maintain large-scale healthcare databases, including the collection, cleaning, and input of complex data sources such as Electronic Health Records (EHR); Advanced Statistical Analysis: Develop and apply novel statistical methodologies for causal inference, with a focus on techniques such as target trial emulation to evaluate COPD management strategies using observational data; Big Data & Bioinformatics: Perform robust big data and bioinformatics analyses to identify patterns, trends, and insights from large, complex datasets; Research Dissemination & Grant writing: Take a leading role in drafting manuscripts for publication in peer-reviewed journals and in the preparation of competitive grant applications; and, General Duties: Fulfill any other related tasks as assigned by the Principal Investigator and supervisors. Candidates Candidates should possess the following qualifications, experience, and competence: A PhD degree in Biostatistics, Data Science, Epidemiology, Statistics, or a related discipline; A proven publication record in peer-reviewed journals, with first-authorship being a significant advantage; Specific experience working with Electronic Health Records (EHR) or other large-scale healthcare databases; Domain knowledge in COPD, cardiovascular, or cerebrovascular diseases; Experience in contributing to or leading the writing of research grant applications; Proven proficiency in at least one statistical programming language such as R or Python (with scientific libraries like Pandas, NumPy, Scikit-learn); Demonstrated experience in managing, cleaning, and curating large, complex datasets; Familiarity with database structures and SQL is highly desirable; Direct hands-on experience with, or a strong theoretical understanding of, modern causal inference methodologies. This includes, but is not limited to: Target Trial Emulation, clustering, Propensity score matching/weighting, Instrumental variable analysis; Experience in conducting systematic literature reviews and a proven track record of contributing to the drafting of academic manuscripts for publication; Exceptional ability to analyze complex problems, integrate information from different sources, and develop innovative analytical solutions; Meticulous attention to detail is non-negotiable, especially concerning data quality, code accuracy, and manuscript preparation; The ability to work independently, manage one's own time effectively, and take initiative to drive projects forward with minimal supervision; Strong written and verbal communication skills, with the ability to explain complex statistical concepts and research findings to both technical and non-technical team members; and, A demonstrated ability to work effectively as part of a multidisciplinary research team. Duration of Appointment 1 year 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. 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 support research on chronic diseases, focusing on data management, statistical analysis, and dissemination of findings. Responsibilities include conducting literature reviews, managing healthcare databases, and drafting manuscripts for publication.