Join the Evolutionary Epidemiology group at the University of Lausanne 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.

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!

Specifics:
- Duration: 2 years (initial contract for 1 year, but funding is
  available for 2 years)
- Potential for further extension depending on funding
- Start date: ideally September 2026, but there is flexibility in both
  directions
- For more information and to apply: tinyurl.com/6c4y3jke

Your qualifications
- A PhD in a relevant topic, such infectious disease modelling,
  computational biology, physics, or statistics.
- Expertise in either mathematical modelling (including model fitting),
  statistical modelling or machine learning.
- An interest in public health and antibiotic resistance
- Excellent written and oral communication skills in English.

What the position offers you
- An exciting opportunity to shape your research in a supportive and
  stimulating environment.
- Exceptional scope for collaboration through e.g. the NCCR
  Microbiomes network.
- Access to top-notch resources and possibilities for independent
  funding and fellowships.
- Excellent support for further learning and professional development.
- Plenty of opportunities to attend conferences and to build your
  scientific network.
- Attractive salary, beautiful location and excellent quality of life in
  a great city.

Sonja Lehtinen <sonja.lehtinen@unil.ch>

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