Research Fellow

Roles & Responsibilities

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for Research Fellow/Senior Research Fellow 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 here: https://www.healthdata.org/research-analysis/gbd.

Purpose of the post

We seek a highly motivated researcher with strong quantitative skills, passion for global health and a desire to shape health policy through evidence-based research. Appointments will be made on a 1-year or 2-year contract basis in the first instance, with the possibility of extension.

The Research Fellow/Senior Research Fellow will contribute to high-impact global health research by advancing the Global Burden of Disease (GBD) Study's work in ASEAN, the Asia-Pacific and beyond. This role offers an opportunity to shape regional health priorities through rigorous evidence, with strong potential for professional growth in research leadership, policy engagement, and mentorship.

Main duties and responsibilities

The Research Fellow/Senior Research Fellow will:

• Lead GBD research projects, which may include systematic reviews, meta-analyses, and epidemiological disease modelling.
• Set research direction and oversee the design, execution, and analytical planning of projects.
• Lead key publications, including the drafting, development, and submission of manuscripts
• Supervise and mentor junior team members, ensuring quality and methodological rigor.
• Serve as an in-house methodological expert, providing guidance on study design, statistical approaches, and data interpretation.
• Develop subject-matter expertise, taking ownership of thematic areas and leading components of the research program, including cross-university collaborations.
• Engage in policy translation, offering technical consultation to external stakeholders such as ministries of health, multilateral organizations, and NGOs.
• Explore and pursue grant opportunities to expand the research portfolio and impact.

Qualifications

• A MD or PhD in statistics, biostatistics, epidemiology, data science, public health, mathematics, social sciences, or other quantitative disciplines
• Demonstrates interest in global health and health policy
• Strong quantitative competencies and sound judgment in data analysis and interpretation
• Proficiency in R or Python for statistical analysis and modelling
• Experience leading research teams or managing research projects (for Senior Research Fellow role)
• A solid publication track record
• Strong work ethics, communication and leadership skills, with the ability to work in a multidisciplinary, multicultural and fast pace environment

Remuneration will be commensurate with the candidate's qualifications and experience. Informal enquiries are welcome and should be made 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, complete list of publications/oral presentations), cover letter, and full contacts of three (3) referees to the NUS Career Portal.

We regret that only shortlisted candidates will be notified.

Tell employers what skills you have

Public Health
Mathematics
Global Health
Health Policy
Epidemiology
Social Sciences
Python
Statistics
Data Science
Biostatistics

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