Postdoctoral Fellow, Chronic Diseases

Job Description

Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health: Postdoctoral Fellow/Research Associate – Chronic diseases

The Saw Swee Hock School of Public Health (SSHSPH) at the National University of Singapore (NUS) is seeking a Research Fellow (RF) or Research Associate (RA) for the various projects on chronic disease. The successful applicant will have a strong foundation in epidemiology and quantitative methods, show good initiative in troubleshooting tasks and have excellent communication skills. The RF or RA will play an important role in the conduct of current research projects on diabetes epidemiology, care and outcomes. In addition, successful candidates will be expected to support the preparation of new grant proposals. The RF will also be expected to work independently, while working in a team-based setting. 


  • Conduct and coordinate clinical or epidemiologic research under the direction and supervision of the Principal Investigator and Collaborators, including preparing applications for ethical approval, data collection and management, and quality assurance 
  • Manage these research projects in a team-based, cross functional research environment, which include supervising/ mentoring junior research staff and research students 
  • Undertake necessary statistical analysis, including advanced modelling techniques, to interrogate the data 
  • Draft research reports and manuscripts for scientific sharing and publication 
  • Support the preparation of new grant proposals 
  • Attend project meetings and to participate (where necessary) in other meetings 
  • Ensure compliance with health, safety and ethical guidelines in all aspects of work 
  • Undertake any other specific roles and management functions as may be reasonably required by the Principal Investigator 



  • Degree in public health, epidemiology, biostatistics, health services research, health information science or related fields. Master or PhD degree in one of these fields is preferred 
  • Fluency in English and good scientific writing skills as demonstrated by the track record of publications in international peer reviewed journals 
  • Proficiency in the use of statistical software (Stata and R) 
  • Expertise in epidemiological and statistical analysis techniques, including joint modelling for time to event analysis and Markov modelling 
  • Ability to work independently as well as in a team-based, cross functional research environment 
  • Self-motivated, independent learner and detail-oriented 
  • Good project management skills 

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