Research Assistant, Statistical Analysis
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 statistical genetics and multi-omics.
The group focuses on epidemiology of common human diseases and complex traits. The position emphasize on analyses of longitudinal epidemiological data and high-dimensional data derived from high-throughput technologies such as genome-wide genotyping/sequencing, methylation, metabolomics, proteomics to understand the pathogenesis of one or more of these diseases.
One of the primary projects is the Diabetes Study in Nephropathy And other Microvascular Complications (DYNAMO). DYNAMO aims to determine the genes and processes involved in the development of diabetic kidney disease, to identify them for earlier intervention. We have measured genomics, lipidomics and proteomics across diabetic samples in the community and hospitals. Outcomes and phenotypic traits are to be analysed with the multi-omics data to derive insights on the pathways to developing diabetes complications.
Major duties and responsibility of the post includes managing, extracting, analysing data from omics 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)
- File management and data analysis in the Unix/Linux environment
- Perl or Python
- Microsoft Office Applications, particularly MS Word, PowerPoint, Excel (preferably with proficiency in Visual Basic)
The successful applicant is expected to possess at least a Bachelor’s degree in genetics, statistics, computational biology, bioinformatics, computer science or mathematics. Relevant experience in data analyses will be considered.
At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presences are required.
In accordance with Singapore's legal requirements, unvaccinated workers will not be able to work on the NUS premises with effect from 15 January 2022. As such, job applicants will need to be fully COVID-19 vaccinated to secure successful employment with NUS.
Location: Kent Ridge Campus
Organization: National University of Singapore
Department: Saw Swee Hock School of Public Health
Job requisition ID: 12565