Research Assistant / Associate (Health Technology Assessment)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal. NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant-Associate-%28Health-Technology-Assessment%29/33813-en_GB/ We regret that only shortlisted candidates will be notified. Job Description Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health: Research Assistant/Associate (Health Technology Assessment). The Centre of Health Intervention and Policy Evaluation Research (HIPER) at the Saw Swee Hock School of Public Health (SSHSPH), NUS, is seeking to hire research staff with relevant experience to lead and support work on health technology assessment (HTA). The sucsessful candidate will play a critical role in the development of the Centre’s growing research agenda to support health policy and services research in Singapore and the region, gaining the opportunity to work with leading experts and policy makers in the field. The successful candidate will be expected to perform research administration, conduct research, disseminate research findings, and be involved in capacity building through conducting workshops for local and regional participants. As a Researcher of the Centre, you will be presented with various opportunities to further develop your skills to ensure personal growth in your career. Key Responsibilities Research Execution: Conduct rigorous research and lead projects focused on Health Technology Assessment (HTA). Dissemination & Capacity Building: Disseminate research findings through academic publications and reports, and contribute to capacity building by conducting workshops for local and regional participants. Qualifications A relevant master degree in Biostatistics, Health economics, Economics, Pharmacy, Public Health, or a related field. Strong familiarity with the Singapore healthcare ecosystem, national health policies, and local clinical data structures. Preferred Skills & Experience Applicants possessing experience or a strong research interest in any of the following areas are highly encouraged to apply: Clinical/Domain Interests: Pharmaceuticals, medical devices, early HTA, real-world evidence, and value-based care. Health Economic Modelling: Practical experience with Markov cohort models and/or microsimulation. Data Management & Analysis: Proficiency in handling electronic medical records (EMR), clinical trial data, survey data, and observational data. Evidence Synthesis: Experience conducting systematic reviews and meta-analyses. Technical Skills: Proficiency in analytical software such as R, STATA, Excel, or similar tools.