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Research Associate (Modelling and Biostatistics)

Job Description

Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health:

Research Associate (1 year)

We are looking for research associates with a quantitative background for research projects in the areas of Modelling and Biostatistics. They will be working within the team under the Principal Investigator, Associate Professor Alex R Cook and/or Senior Research Fellow Su Park.

Candidates need to be able to understand statistical modelling, have a strong mathematical background, and be fluent in R programming or Python coding. The candidate will be working with the Principal Investigator(s) on the analysis of big health data, utilising an array of methods to infer statistical relationships and health outcomes. Further mathematical modelling will also be carried out when necessary.

Responsibilities:

  • Analysing data using statistical and mathematical modelling techniques
  • Academic writing and publication of results
  • Preparation of meeting materials for stakeholders

Qualifications

Requirements:

  • Master in a quantitative discipline (economics, quantitative finances, statistics, pharmacy, mathematics, data science, computational biology, operational research, computer science, bioinformatics).
  • Two years of working experience
  • Very proficient in Statistical Software (R preferred)
  • Proficient in other programming languages such as Python is a plus
  • Excellent written and oral communication skills
  • Good organizational and administrative skills

Applicants should include a brief statement of interest, CV, list of publications (if applicable) and the names and email details of 3 referees who may be contacted immediately if shortlisted.

Recruitment is open immediately and will continue until all positions are filled.

Qualifications

Master in a quantitative discipline (economics, quantitative finances, statistics, pharmacy, mathematics, data science, computational biology, operational research, computer science, bioinformatics).

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