Research Assistant (AMR Modelling)
Date: 8 Nov 2023
Location: SSHSPH, Kent Ridge Campus, SG
Company: National University of Singapore
Job Description
Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health:
Research Assistant (AMR Modelling)
Job Description
The Health Intervention and Policy Evaluation Research (HIPER) team in the Saw Swee Hock School of Public Health, NUS is seeking a Research Assistant to undertake a research project in antimicrobial resistance modelling.
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 model development and refinement. Job responsibilities include:
• Analysing data using mathematical modelling techniques
• Academic writing and publication of results
• Preparation of meeting materials for stakeholders
This is a full-time position with 1-year contract that may be renewed.
Qualifications
• Masters or PhD in a quantitative discipline (economics, quantitative finances, statistics, pharmacy, mathematics, data science, computational biology, operational research, computer science, bioinformatics).
• 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.
For further enquiries, please contact Ms Chua Hui Lan (ephchl@nus.edu.sg).
Recruitment is open immediately and will continue until all positions are filled.
We regret that only shortlisted candidates will be notified.
Qualifications
Masters or PhD in a quantitative discipline (economics, quantitative finances, statistics, pharmacy, mathematics, data science, computational biology, operational research, computer science, bioinformatics).