We are looking for two postdoctoral researchers to join our team at the intersection of evolutionary theory, microbial ecology and public health. We use mathematical and statistical modelling to draw insights from genomic and epidemiological data; address problems in public health; and answer fundamental questions about bacterial ecology and evolution.

Join us in developing approaches to predicting the spread of antibiotic resistance at the host population scale. We are interested in translating fundamental evolutionary insights into robust predictions about the real-world behaviour of resistance frequencies. We are looking for researchers to collaboratively shape this project through several possible directions:

• Epidemiological modelling: Developing hybrid mechanistic-statistical models of resistance dynamics.
• Data-driven prediction: Using statistical modelling, causal inference, or machine learning to forecast resistance trends.
• Fitness estimation: Inferring the fitness impacts of resistance determinants using surveillance and genomic data.

The Evolutionary Epidemiology group is based at the University of Lausanne’s Computational Biology Department. We are also affiliated with the NCCR Microbiomes, providing fantastic opportunities for collaborations with experimental, clinical and other modelling groups. The group is very friendly, with people from diverse backgrounds working on a range of projects relating to microbial evolution and dynamics.

We’re looking for curious, collaborative and thoughtful researchers. The envisioned topic is antibiotic resistance, but there is some flexibility: if you are interested in other aspects of evolutionary epidemiology, don’t hesitate to get in touch. If you like our papers, we want to hear from you!