Research Assistant, Population Health and Modelling Metrics
Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health:
Research Assistant x 1 (1 year minimum, up to 3 years)
A research assistant position is available in the Saw Swee Hock School of Public Health to support the Principal Investigators in research projects in the areas of Population Health and Modelling Metrics.
The group focuses on epidemiology of common human diseases and complex traits. Major duties and responsibility of the post includes managing, extracting, analysing and document data from databases or raw datasets. In addition, candidate is required to do report writing, presentations, and publication of results and findings in peer-reviewed journals. Furthermore, he/she will need to contribute to development and writing of research grant proposals.
Candidate must be an independent mature worker who is well-organized and has an eye for details.
Candidate must possess excellent written and verbal communication skills. He/she must possess the ability to work effectively with colleagues to achieve team goals. Good proficiency in the following areas is essential:
- Statistical software (R)
- Microsoft Office Applications, particularly MS Word, PowerPoint, Excel (preferably with proficiency in Visual Basic)
Good proficiency and experience in the following areas is preferred:
- Stata and/or SPSS
- Oracle database creation and configuration
- Experience with data extraction with Oracle
- Experience with the PL-SQL, Oracle database
Recruitment is open immediately, and will continue until the position is filled. Applicants should send a brief statement of interest, CV, three named references, and other supporting documents together with the application.
We regret that only shortlisted candidates will be notified.
The successful applicant is expected to possess at least a Bachelor’s or Master’s Degree in Statistics. Alternatively, Bachelor Degree in Computer Science or Mathematics, with relevant experience in data science may be considered.