Big Data Institute, Old Road Campus, Oxford, OX3 7LF
Postdoctoral Data Scientist
I currently work on identifying morphological signatures of metastasis in prostate cancer, using AI and image analysis. Metastasis can lead to more aggressive forms of cancers, so that early and precise identification of metastasis, or lack thereof, can help avoiding heavy and costly treatments.
I also combine mathematical models describing the evolutionary dynamics of cancerous cells with tissue images obtained from biopsies to learn the drivers of cancer progression. These models will help further our understanding of how the morphology of the tissue changes with cancer stage, and how this is underpinned by changes in the biology and structure of cell communities.
My background is in mathematical modelling and evolutionary biology. I obtained a BSc in Life Sciences at Université Pierre et Marie Curie in 2013, and an MSc in Evolutionary Biology in 2017 at Ecole normale supérieure, Ulm.
I completed a PhD in Mathematical Biology at the University of Oxford in 2021, during which I developed neural ordinary differential equation models to study feedbacks between ecological and evolutionary change in natural systems, such as in Darwin’s finches.
Comparison of size-structured and species-level trophic networks reveals antagonistic effects of temperature on vertical trophic diversity at the population and species level
Bonnaffé W. et al, (2021), Oikos
Neural ordinary differential equations for ecological and evolutionary time-series analysis
Bonnaffé W. et al, (2021), Methods in Ecology and Evolution