Research Associate (HSRPH/SS)

National University of Singapore

Singapore

On-site

SGD 40,000 - 60,000

Full time

14 days+

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Job summary

The National University of Singapore is seeking a Research Assistant for the Duke-NUS Medical School. The successful candidate will engage in data cleaning and analysis, assist in research manuscript preparation, and support project management activities. Ideal candidates will possess a Bachelor’s Degree with a preference for statistics or data science, along with a minimum of 2 years of quantitative data experience. Strong communication skills and the ability to work with large datasets are essential. This role offers exposure to innovative health research and collaboration with multiple stakeholders.

Qualifications

  • Bachelor’s Degree in any discipline preferred in statistics, economics, data science, public health, or epidemiology.
  • Minimum 2 years of experience with quantitative data.
  • Strong quantitative skills for handling large data sets.

Responsibilities

  • Perform data cleaning, handling and analysis.
  • Assist in drafting research abstracts and manuscripts.
  • Conduct literature reviews to evaluate health innovations.

Skills

Quantitative skills
Data handling
Communication
Teamwork

Education

Bachelor’s Degree

Tools

R programming

Job description

Job Title: Research Assistant (HSRPH/SS)

University-Level Unit: Duke-NUS Medical School

Faculty/Department-Level Unit: Office of Research

Employee Category: Research Staff

Location_ONB: Outram Campus

Posting Start Date: 28/04/2026

Job Overview

Duke-NUS embodies a strategic partnership between Duke University and National University of Singapore (NUS). It works closely with the Singapore Health Services (SingHealth) cluster which is a network of national specialty disease centres, hospitals and polyclinics, to advance medicine and improve lives through cutting-edge research and education. Together, Duke-NUS and SingHealth form an Academic Medical Centre that comprises a number of academic collaborations.

The Signature Research Programme in Health Services Research & Population Health (“HSRPH”) in Duke-NUS Medical School is a centre of academic excellence for research and education of health systems and services for the population in Singapore and beyond. Our research methods include implementation science, health economics, decision science, survey/qualitative research, quantitative medicine, epidemiology, and data science. The population health outcomes programme Duke-NUS has established provides a framework for evaluating and improving healthcare delivery systems nationwide. We are also developing a range of educational activities for healthcare professionals including short courses, graduate certificates, Masters course and PhD programmes.

Job Description
  • Perform data cleaning, handling and analysis
  • Assist in drafting research abstracts and manuscripts
  • Assist in preparation of PowerPoint presentations to various stakeholders
  • Conduct literature reviews to evaluate the potential value of health innovations
  • Assist in preparation of evaluation reports for the health economics team
  • Extract data from existing databases and published literature
  • Support project management activities across different stages of research, including development of study objectives, study design, data extraction, data collation, statistical analysis, modelling, and stakeholder engagement, under guidance from senior team members.
  • Support secretariat and administrative functions pertaining to the health economics team at HSRPH
Qualifications
  • Bachelor’s Degree in any discipline. Candidate with training in statistics, economics, data science, public health, epidemiology, or related disciplines, and with strong quantitative skills is preferred.
  • Minimum 2 years of working experiences with quantitative data
  • Adept at working with data, including processing raw data to visualise trends and deciphering patterns and ability to handle large data sets
  • Experience in various quantitative research methods is preferred.
  • Experience with R programming language, and willing to learn more applications
  • Excellent verbal and written communication and interpersonal skills
  • Able to work in a team, with dynamic reporting lines and multiple stakeholders
  • Able to work independently with limited supervision
  • Individual who is action-oriented, highly motivated and target-focused

We regret that only shortlisted candidates will be notified.

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