Job Description

The National University of Singapore invites applications for Research Fellow (SF) / Senior Research Fellow (SRF) 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 one- or two-year contract basis in the first instance, with the possibility of extension.

The RF 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, including through the adoption of cutting-edge AI and data-science methods in disease burden estimation.

Main duties and responsibilities

The RF / SRF 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
• Integrate AI-assisted tools into research workflows- including AI code-generation assistants, automated data-quality checks, anomaly detection, and LLM/NLP-based pipelines for literature screening and evidence synthesis to improve efficiency, reproducibility and scalability of research

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
• Hands-on experience using AI and machine-learning tools in a data-science or research context, e.g. building predictive models with machine-learning frameworks or deploying LLM-based workflows for data extraction and synthesis
• Experience leading research teams or managing research projects and supervising junior researcher (for SRF role)
• A solid publication track record
• Strong communication skills, with the ability to translate complex technical work for non-technical audiences
• Strong work ethic, with the ability to work in a multidisciplinary, multicultural, fast-paced 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 this 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 : 29978