Research Fellow (Behavioural Epidemiology & Digital Health)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal. NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Behavioural-Epidemiology-&-Digital-Health%29/32883-en_GB/?st=8C544B8BD7DCBD0702CEBC96D1619F2D920A815F We regret that only shortlisted candidates will be notified. Job Description The Saw Swee Hock School of Public Health (SSHSPH), National University of Singapore, invites applications for Research Fellow positions within the PANDA programme. We are seeking experienced, self-driven researchers with a strong grounding in behavioural epidemiology, digital health, or related disciplines to contribute to innovative research at the interface of wearable and sensor-based health measurement, behavioural science, digital health, and epidemiology. Successful candidates will take an independent and substantive role in the design, conduct, and dissemination of research. The programme offers a rich environment for academic development, with access to large-scale longitudinal cohorts, wearable and sensor-based data, and digital behavioural intervention platforms across diverse Asian populations. About PANDA The Physical Activity and Nutrition Determinants in Asia (PANDA) programme is one of the flagship research programmes at SSHSPH, bringing together faculty from public health, epidemiology, psychology, medicine, and data science. We have conducted research using accelerometers, wearable activity trackers, ecological momentary assessment, and digital phenotyping approaches to better understand movement behaviours, lifestyle patterns, and their associations with physical and mental health outcomes across the life course. With these, we aim to understand the behavioural, social, environmental, and biological determinants of physical activity and nutrition in Asian populations, and to develop and evaluate digital and community-based interventions that promote healthy behaviours and prevent non-communicable diseases and support mental well-being. Key Responsibilities Contribute to the processing and interpretation of wearable-derived physical activity and behavioural datasets Design and conduct epidemiological studies and behavioural research examining physical activity, sedentary behaviour, sleep, and related health behaviours using wearable and sensor-derived data in population-based and intervention settings Develop, implement, and evaluate digital health interventions (e.g., app-based, wearable-supported, or mHealth platforms) targeting health behaviour change Analyse complex longitudinal, sensor-derived, and ecological momentary assessment (EMA) datasets using appropriate epidemiological and statistical methods Lead or contribute to systematic reviews, intervention evaluations, and mixed-methods research relevant to behavioural epidemiology and digital health Take a leading role in the preparation of peer-reviewed scientific manuscripts, with first or senior authorship commensurate with contribution Contribute to the development of research protocols, ethics applications, and grant proposals in collaboration with the research team Contribute to the supervision and mentorship of junior research staff and postgraduate students where appropriate Present research findings at national and international conferences and engage with broader academic and policy communities Qualifications Requirements A PhD degree (with substantial research experience) in Public Health, Epidemiology, Health Psychology, Behavioural Science, or a closely related field Demonstrated track record of independent research, including peer-reviewed publications in behavioural epidemiology, digital health, health behaviour change, or related areas Solid grounding in epidemiological and/or behavioural research methods; experience linking physical activity or movement behaviour data with cardiometabolic, mental health, or other health outcomes is advantageous Familiarity with digital health tools, mHealth technologies, wearable devices, or ecological momentary assessment is desirable Proficiency in statistical analysis; experience with R, Stata, Python, or equivalent Excellent scientific writing skills and a demonstrated ability to lead manuscript preparation Strong interpersonal and communication skills; ability to work effectively in a multidisciplinary team and independently manage research projects A proactive, collaborative…