Research Assistant

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading academic institution in Singapore is seeking Research Assistants, Associates, and Fellows for interdisciplinary projects in public health. The successful candidates will manage and analyze complex datasets using modern statistical approaches. Roles include participating in research coordination and contributing to academic publications. Ideal for those building a career in quantitative public health and data science. Positions are open immediately and will remain until filled.

Qualifications

• Strong quantitative and computational skills.
• Demonstrated interest in academic output generation.
• Experience with complex datasets is an advantage.

Responsibilities

• Coordinate interdisciplinary research projects.
• Conduct data management and quantitative analysis.
• Contribute to research presentations and manuscripts.

Skills

Quantitative skills

Analytical skills

Data management

Interpersonal skills

Communication skills

Education

Degree in Public Health, Epidemiology, Psychology, Data Science, Computer Science, Statistics, or related field

Job description

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

Research Assistant / Research Associate / Research Fellow

The Saw Swee Hock School of Public Health (SSHSPH), National University of Singapore, invites applications for Research Assistant, Research Associate, and Research Fellow positions to support interdisciplinary projects within the PANDA programme. We are seeking highly motivated colleagues with strong quantitative and analytical skills to contribute to the coordination of research activities and/or the management and analysis of complex research data.

These positions offer the opportunity to work in a collaborative academic research environment at the intersection of public health, behavioural science, and digital health technologies. Candidates will have the opportunity to engage with large-scale, high‑resolution datasets derived from wearable devices, sensors, and other digital health tools using modern statistical and data science approaches, and take a substantive role in the development of peer-reviewed scientific manuscripts, with opportunities for lead or co‑authorship depending on contribution.

Key Responsibilities

• Contribute to the planning, coordination, and implementation of interdisciplinary research projects, including participant recruitment, onboarding, and data collection
• Take an active role in data management, processing, and quantitative analysis (e.g., longitudinal and multilevel modelling, time‑series or high‑frequency data analysis, machine learning or predictive modelling) of complex longitudinal and sensor‑derived datasets
• Contribute to the development of analysis plans and methodological approaches in collaboration with the research team
• Lead or contribute to the preparation of research presentations, grant applications, and scientific manuscripts for peer‑reviewed journals

Successful candidates will work closely with members of the Physical Activity and Nutrition Determinants in Asia (PANDA) research programme. PANDA is one of the major research programmes at SSHSPH and brings together faculty from multiple disciplines. The programme aims to understand the determinants of nutrition and physical activity behaviours in Asian populations and to develop interventions that improve these behaviours and contribute to the prevention of non‑communicable diseases and the promotion of mental well‑being.

Requirements

• A relevant degree in Public Health, Epidemiology, Psychology, Data Science, Computer Science, Statistics, or a related field
• Strong quantitative and computational skills and understanding of statistical or data‑analytic methods
• Prior experience in academic or health‑related research coordination is an advantage
• Experience or strong interest in working with complex datasets (e.g., wearable, sensor‑based, or longitudinal data)
• Demonstrated interest in academic output generation, including scientific publications, conference presentations, and grant writing
• Strong interpersonal and communication skills, with the ability to work independently and as part of a multidisciplinary team
• Well‑organised, detail‑oriented, and able to manage multiple tasks and timelines; a proactive, solution‑oriented mindset in dynamic research environments
• The position is particularly well suited for candidates seeking to build a career in quantitative public health, behavioural data science, or digital health analytics, and who are interested in developing advanced analytical expertise, a strong publication record, and experience working with complex real‑world data

Recruitment is open immediately and will continue until the positions are filled.

Only shortlisted candidates will be notified.