Contacts

Aimée Altermatt

Research Assistant

Background

Aimée is a research assistant working on the Modelling and Biostatistics team and the Optimise Study. She applies her knowledge of mathematics and computer science to modelling COVID-19 and other infectious diseases in various countries. In her position on the Data Analysis team of the Optimise Study, she assists in the analysis, preparation, and planning of monthly Optimise reports, which inform government policy. She also contributes to the survey design, data analysis and output of Snapshot Surveys and Snapshot Reports which inform government policy.

She has also applied her French language skills to her modelling work, translating a nutrition model from English to French in order to reach a wider audience.

Aimée graduated from the University of Melbourne in 2020, where she concurrently studied Applied Mathematics and French. During her university studies, she combined her passions for mathematics and French through research and translation projects in Metropolitan France, New Caledonia and Melbourne and completed an exchange semester in Geneva, Switzerland, where she undertook an internship in data processing and analysis. In 2022, she began her Masters in Health Data Analytics at Monash University, a course that will allow her to further explore her interests in computer science and public health.

Positions

  • Research Assistant, Burnet Institute, September 2020 – present
  • French Grammar Technical Support, The University of Melbourne, September – December 2021
  • Project Liaison Officer, Why Learn French? Project, March – July 2021
  • Senior ESG Analyst Intern, Covalence, Geneva, August – October 2020
  • French Language Assistant, Academy of Mary Immaculate, May 2016 – November 2019

Qualifications

  • Ongoing: Masters in Health Data Analytics, Monash University
  • 2020: BSc, University of Melbourne, Australia major in mathematics and statistics
  • 2020: Diploma in Languages (French), University of Melbourne, Australia

Projects (1)

Current (1)

  • The Optimise Study: Optimising Isolation, Quarantine and Distancing for COVID-19

Publications (9)

2022 (1)

2021 (8)