Research Assistant (AMR Modelling)
- Recruiter
- NATIONAL UNIVERSITY OF SINGAPORE
- Location
- Singapore
- Posted
- 29 Nov 2023
- End of advertisement period
- 29 Dec 2023
- Ref
- 16318544
- Academic Discipline
- Business & Economics, Accounting & Finance, Economics & Econometrics, Engineering & Technology, Computer Science, Life sciences, Biological Sciences, Physical Sciences, Mathematics & Statistics
- Contract Type
- Fixed Term
- Hours
- Full Time
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).