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Research Associate (CARE/Quantitative Research)

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Date: 14-Oct-2021

Location: Outram Campus, SG

Company: National University of Singapore

Job Responsibilities

 

The Centre for Ageing Research and Education (CARE) is an academic research centre based in Duke-NUS Medical School. Drawing on its interdisciplinary expertise and collaborations across medical, social, psychological, economic and environmental perspectives, CARE conducts research on the social and medical determinants of successful ageing, and actively engages with government and industry partners to identify needs and strategies to enhance the experience of ageing in Singapore. CARE is a vibrant work place with individuals from diverse academic and personal backgrounds and range of interests. We value 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.

 

The selected candidate will work with other researchers at CARE on several projects with the primary responsibilities including but not limited to the following: -

  • Conduct quantitative analysis of CARE’s survey data using Stata, SAS, or R.
  • Write and edit research papers, policy and research briefs, and prepare presentations.
  • Contribute to the development of grant applications and research proposals.
  • Present research findings to academic and non-academic audiences.
  • Support project management tasks including questionnaire development, managing project documentation, preparing reports and coordinating with survey research firms and other agencies.
  • Assist with CARE’s other initiatives where required.

JOb Requirements

 

  • Master’s Degree in Sociology, Economics, Epidemiology, Gerontology, Public Health, Psychology, Social Work, or other related disciplines.
  • Minimum 2 years of relevant work experience; candidates whose relevant work experience does not meet the minimum required years will be considered for a Research Assistant (Senior) position.
  • Prior experience in quantitative data analysis of individual-level data.
  • Possess excellent written and oral communication skills in English.
  • Motivated and detail-oriented with the ability to work independently as well as with others in a multi-disciplinary setting.
  • Able to manage multiple tasks simultaneously.

 

Interested applicants may apply and submit following documents: CV, a letter of interest, and names and contact information of 2 academic referees. Applications will be reviewed on a rolling basis.

 

We regret that only shortlisted applicants will be notified.