Job Description
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 2 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 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.
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:
1. Statistical software (R)
2. File management and data analysis in the Unix/Linux environment
3. Perl or Python
4. Microsoft Office Applications, particularly MS Word, PowerPoint, Excel (preferably with proficiency in Visual Basic)
Recruitment is open immediately, and will continue until the position is filled.
For further enquiries, please contact Dr Sim Xueling at [email protected].
We regret that only shortlisted candidates will be notified.
Qualifications
The successful applicant is expected to possess at least a Bachelor’s in genetics, statistics, computational biology, or bioinformatics. Alternatively, Bachelor Degree in Computer Science or Mathematics, with relevant experience in data science may be considered.
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