Deskripsi Pekerjaan
The National University of Singapore (NUS) is seeking a highly motivated and skilled Research Fellow or Senior Research Fellow (Quantitative) to join the Centre for Ageing Research and Education (CARE). This is a unique opportunity to contribute to high-impact research aimed at understanding the complexities of healthy ageing in a rapidly evolving societal landscape.
As part of our interdisciplinary team, you will lead and support quantitative research projects, focusing on data-driven insights that inform public policy and clinical practice. The successful candidate will leverage advanced statistical methodologies to analyze large-scale datasets, contributing to our mission of improving the quality of life for older adults in Singapore and beyond.
You will work in a collaborative environment alongside world-class academics, with access to robust resources and a supportive research community. We are looking for a rigorous, detail-oriented researcher with a passion for evidence-based solutions in the longevity and health sector.
Tanggung Jawab
- Design and execute quantitative research protocols for studies on healthy ageing and longevity.
- Perform advanced statistical modeling, data cleaning, and longitudinal analysis of complex datasets.
- Lead the drafting of high-impact peer-reviewed publications and conference presentations.
- Collaborate with interdisciplinary teams, including sociologists, clinicians, and health policy experts.
- Supervise junior researchers and assist in mentoring postgraduate students within the department.
- Manage project timelines, ensuring deliverables meet institutional and funding requirements.
- Contribute to grant writing and research funding applications to support ongoing initiatives.
Kualifikasi
- PhD in Statistics, Economics, Epidemiology, Public Health, Quantitative Social Sciences, or a related field.
- Proven track record of research excellence with publications in reputable journals.
- Expertise in statistical software such as R, Stata, Python, or SAS.
- Strong background in longitudinal data analysis, survival analysis, or mixed-methods modeling.
- Experience in managing and analyzing large administrative or longitudinal survey datasets.
- Excellent verbal and written communication skills for academic and public-facing reports.
- Ability to work independently and manage complex research trajectories in a dynamic environment.