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Research Assistant
4 weeks ago
Interested applicants are invited to apply directly at the NUS Career Portal.
Your application will be processed only if you apply via NUS Career Portal.
We regret that only shortlisted candidates will be notified.
Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health at the National University of Singapore (NUS):
Research Assistant
We are looking for a full-time research assistant to support data analysis for various research projects on cancer and public health. The successful candidate will work closely with a team of epidemiologists, health economists and clinicians, and will have the opportunity to gain hands-on experience in analysing national health datasets to address issues related to cancer care and population health.
Responsibilities:
• Assist with the study design, literature review, and ethics approval
• Check data accuracy and completeness and conduct data cleaning, harmonization and linkage
• Analyse research data via basic and advanced statistical methods, according to the PI’s research directions
• Develop data visualization and written reports for presentation and communicate research findings with internal and external stakeholders
• Prepare research reports/manuscripts
Requirements:
• a BSc in a quantitative discipline (statistics, mathematics, computational biology, data science)
• Strong skills in statistical and data analytics software (knowledge of R is essential)
• Meticulous, possess good interpersonal and organising skills
• Able to work independently as well as in a team
• Track record of scientific publication and leading projects is advantageous
Recruitment is open immediately and will continue until the position is filled. Applicants should send the following documents during the job application:
1. Cover letter highlighting career goals and relevant experience
2. Curriculum Vitae, containing details of three named referees
Tell employers what skills you have
Data Analysis
Public Health
Mathematics
Population Health
Statistics
Computational Biology
Data Science
Data Analytics
Able To Work Independently
Data Visualization
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