You can find more detailed information on our research here (or click on the figures below for examples).
You will develop machine-learning algorithms tailored to the needs of synthetic biology, enabling the production of renewable bioproducts through predictive bioengineering. The incumbent will focus on the development of “Explainable AI” (XAI) technologies, leveraging Deep Learning and other ensemble strategies in collaboration with Ben Brown. You will work as part of a collaborative team to integrate microbial phenotypic data (e.g. fluxomics, transcriptomics, proteomics, and metabolomics) into quantitative computational models able to predict and explain the outcomes of bioengineering interventions.