PhD Position Geospatial Modelling of Antimicrobial Resistance in Animals

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Antimicrobial Resistance (AMR) - the ability of microbes to evolve and resist treatment - is rising globally. This slow‑moving crisis is driven by the overuse of drugs in humans, but also in animal production, which currently represents 73% of global antimicrobial consumption. Maps can play a key role in helping to prioritize surveillance efforts and allocate resources to curb animal‑AMR.

In particular, this PhD project will focus on:

• ensemble forecasting from multiple geospatial models,
• expansion of geospatial models in the space‑time dimensions,
• propagation of uncertainty in geospatial models, including positional uncertainty of surveys.

The project will leverage existing global datasets (resistancebank.org). The candidate will also bring their own original research questions to develop in the field of spatial epidemiology. In the Epidemiology & Geography Group, we deeply care about bringing together people from diverse educational backgrounds, geographical areas, and cultural origins to build complementarities within the team.

We are looking for an enthusiastic and quantitatively minded scholar. The candidate must hold a Master’s degree in machine learning, microbiology, epidemiology or related, and have great oral and written communication skills in English.

The ideal candidate will have:

• experience with ensemble forecasting and a strong background in statistics.
• experience working with the programming language R or Python, including the use of species distribution models and spatial analysis packages.

Although not mandatory, the following skills would be an asset:

• experience using high‑performance computing clusters
• experience in conducting systematic literature reviews
• ability to read Mandarin Chinese, Spanish, Portuguese, or Arabic.