Job Description

The National University of Singapore (NUS) invites applications for the position of Research Associate as part of a collaborative partnership between the Institute for Health Metrics and Evaluation (IHME) at the University of Washington and the NUS Yong Loo Lin School of Medicine. The successful candidate will contribute to the Global Burden of Disease (GBD) Study, a landmark international research effort that produces robust, timely, and comparable estimates of health loss due to diseases, injuries, and risk factors worldwide. This role offers an opportunity to be part of a global network advancing data-driven health policy and research impact. More information about the study can be found at: https://www.healthdata.org/research-analysis/gbd.

Purpose of the Post

We seek a motivated and methodical researcher with a strong sense of analytical rigor, who is enthusiastic about applying data to real-world public health challenges and informing evidence-based policy. Appointments will be made on a 1-year or 2-year contract basis in the first instance, with the possibility of extension.

The Research Associate will report to and work closely with the Principal Investigator and study team members to support the successful implementation of ongoing research cycles under the GBD Study. The primary responsibilities will include conducting systematic reviews, performing data extraction and preparation, supporting quantitative data analysis, interpreting and critically appraising results, and contributing to the dissemination of findings to key stakeholders.

Main Duties and Responsibilities

The Research Associate will:

• Conduct systematic reviews and support data extraction, cleaning, and quality-checking in preparation for analysis.
• Support data analysis, including descriptive statistics, generation of graphs, tables, maps, and other innovative figures to visualise health data.
• Interpret and critically appraise analytical results, including cross-checking outputs against existing evidence, identifying implausible estimates, and investigating discrepancies before accepting findings.
• Plan and execute analyses in a structured and reproducible manner, maintaining clear documentation to support team-wide auditability and continuity.
• Contribute to key publications, including the development of manuscripts and associated publication materials.
• Assist in external engagement efforts, providing analytical and visualization support to local and regional partners, including the Ministries of Health and multilateral agencies across Asia.
• Assist with any other duties of a similar nature as delegated by the Principal Investigator.

Qualifications

The following qualifications and competencies are required or preferred:

Academic Background

• Master’s degree in epidemiology, public health, biostatistics, statistics, mathematics, social sciences, medicine, or other quantitative disciplines.
• Basic working knowledge of epidemiological measures (e.g. incidence, prevalence, mortality rates, age-standardized rates, disability-adjusted life years) is required.
• Prior research experience is an advantage but is not strictly required.

Analytical & Technical Skills

• Proficiency in R or Python for data wrangling, analysis, and visualization. Candidates should be able to demonstrate an understanding of the logic and validity of their analytical steps, not only the mechanics of running code.
• Familiarity with statistical concepts, including measures of central tendency, regression models, uncertainty estimation, and data quality assessment.
• Familiarity with systematic review methods and databases (e.g. PRISMA, PubMed, Embase) is an advantage; full training will be provided.

Analytical Thinking & Scientific Rigor

• Ability to break a research question into clearly sequenced analytical tasks, anticipate where errors are most likely to arise, and document processes for reproducibility.
• Willingness to interrogate results critically, rather than accepting outputs at face value, and to investigate further when findings are surprising or inconsistent with prior evidence.

Communication

• Strong written and verbal communication skills, including the ability to organize and structure scientific write-ups clearly.
• Detail-oriented, organized, and able to work both independently and collaboratively.

Professional Attributes

• Comfortable using AI-assisted tools (e.g. AI-assisted coding, literature screening) as productivity aids, with an understanding of their limitations and the continued need to verify outputs independently.
• Possesses a strong sense of responsibility, intellectual curiosity, and professionalism.
• Strong interest in global health and health policy.

Remuneration will be commensurate with the candidate’s qualifications and experience. Informal enquiries are welcome and should be directed to A/Prof Marie Ng at marieng@nus.edu.sg.

Formal application: Please submit your application indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, a complete list of publications/oral presentations, and full contact details for three (3) referees) to the job portal.

We regret that only shortlisted candidates will be notified.

More Information

Location: Kent Ridge Campus

Organization: Yong Loo Lin School of Medicine

Department : Dean-Med-Global Centre for Asian Women’s Health

Employee Referral Eligible: No

Job requisition ID : 29977