Research Associate

19 Jun 2020
End of advertisement period
19 Jul 2020

Lee Kong Chian School of Medicine invites applications for:

Research Associate (Clinical/Medical) in the Centre for Population Health Sciences (A/Prof Josip Car)

We are currently recruiting a Research Associate who will join the Centre for Population Health Sciences at Lee Kong Chian School of Medicine, a joint medical school between Imperial College London and Nanyang Technological University (NTU).

The Centre’s focus areas of research include population health, digital health, mHealth, digital education, and health services and outcomes research.

For more information, please visit:

Reporting to the Director of the Centre for Population Health Sciences, A/Prof Josip Car, responsibilities include:

  • Contributing to and/or managing project teams in a range of multidisciplinary projects (e.g. health systems science, population health, digital health, mHealth)
  • Executing research activities such as data collection, data management, statistical analysis, and collaborator liaison, independently and/or under the direction of senior researchers
  • Assisting senior researchers with preparation of research deliverables including writing progress/final reports and drafting manuscripts for publication in peer-reviewed journals
  • Participating in research seminars and regular team meetings and discussions
  • Performing administrative duties as assigned.

In addition, the selected candidate will undertake ad-hoc assignments or projects where required, as assigned by the Centre Director.

Skills and qualifications:

  • Master’s in clinical sciences, medicine, pharmacology, nursing, medical sciences, digital health, or related disciplines, is required.
  • Experience in the practice of medicine and/or in clinical research.
  • Competent in research design (quantitative, qualitative and mixed methods).
  • Strong statistics grounding.
  • Knowledgeable in medicine, health promotion and education, disease management, health systems science, and mobile learning.
  • Strong project implementation skills including data collection, data management and IRB processes.
  • Project management skills to meet deliverable timelines and quality standards.


  • Highly motivated, meticulous and well organized.
  • Able to work independently and collaborate effectively in a highly diverse, multi-cultural and interdisciplinary team.
  • Adaptable and willing to enter into deep learning in new areas.
  • Fluent in written and spoken English with good communication skills.

Application Procedure:

If you are interested to pursue a career with the School, please apply by submitting your cover letter, CV (including list of publications), and expected salary via the “Apply Now” link below. Only full applications will be considered, and shortlisted candidates will be notified.

Closing date: Interviews will be conducted on a rolling basis.

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