Job Description
The Centre for Ageing Research & Education (CARE) is an academic research centre in Duke-NUS Medical School, Singapore. Drawing on the team's multidisciplinary expertise and collaborations across medical, social, psychological, economic, and environmental perspectives, CARE's research is situated in eight broad thematic areas: Population Health, Social and Psychological Aspects of Ageing, Family Caregiving, Productive Ageing, Falls Prevention, Community-Based Health and Social Care Services, Ageing and the Environment, and Health Communication.
CARE is a vibrant centre with individuals from diverse academic and personal backgrounds, and values the energy, passion, and thought leadership of promising scholars who desire to achieve health, social inclusion, and a high quality of life for older adults in Singapore.
We are seeking a full-time Research Fellow to join our team at CARE. The successful candidate will contribute to uplifting CARE’s existing ageing research cohort datasets to FAIR principles (i.e., Findable, Accessible, Interoperable and Reusable), prepare data and processes to enable linkage and secondary use and generate new insights from use cases through data linkage with other datasets on TRUST (Trusted Research and Real world-data Utilisation and Sharing Tech), a national linkage platform for health-related research.
The primary responsibilities include, but are not limited to the following:
- Serve as the dedicated cohort data manager, and to lead the extraction, management and preparation of cohort datasets for research requests.
- Undertake standardisation and harmonisation of cohort datasets.
- Contribute to the development, maintenance and enhancement of cohort codebooks and data dictionaries.
- Support the development and implementation of data governance framework, policies and standard operating procedures for cohort datasets.
- Contribute to data preparation for ingestion into the TRUST platform, including alignment with relevant data standards and interoperability requirements.
- Lead longitudinal analyses using the harmonised research cohort and TRUST platform data to examine trajectories of health, ageing, and related outcomes over time.
- Maintain comprehensive documentation in line with Human Biomedical Research Act (HBRA) and assist in ethics approval applications and reporting to Institutional Review Boards (IRBs) and funding agencies.
- Lead key research outputs, including publications and conference presentations.
- Contribute to the preparation and development of competitive grant proposals.
- Participate in and support CARE’s education activities including seminars and workshops.
Job Requirements
- PhD in a quantitative health discipline (Epidemiology, Public Health, Medicine, Biostatistics, Health/Clinical Informatics, Pharmacy, Geriatrics/Gerontology, Psychology).
- Experience in gerontology/geriatric or ageing research, with understanding of common geriatric syndromes such as falls, fractures, dementia, and chronic pain.
- Proven ability to conduct independent research, publish high-quality work, and collaborate effectively.
- Proven ability to analyse large, complex healthcare datasets with real world data experience an advantage (e.g., administrative, electronic medical record [EMR], registry, claims data).
- Familiar with advanced longitudinal analysis for understanding transitions in health states over time.
- Strong statistical programming skills, preferably in R.
- Excellent written and verbal communication skills.
- Strong organisational and project management skills.
Desirable - Knowledge of data standardisation and harmonisation methods and common data models (e.g. OMOP CDM).
Interested applicants should fill up the online application on the Duke-NUS website. Please attach the following:
- Cover letter stating your interest in the position (no more than 500 words).
- A Curriculum Vitae (not more than 5 pages), including the contact details of three named referees.
- Writing sample (single - or first-authored academic manuscript, published or unpublished).
Only shortlisted applicants will be notified
