Dr Magdalena Strauss

I joined the University of Exeter in September 2024 as a lecturer in Mathematics and Statistics. Previously, I was a Sir Henry Wellcome fellow based at the European Bioinformatics Institute EMBL-EBI in Cambridge. 

My research interests are at the crossroads of statistics, machine Learning, biology and health science. I am particularly interested in cellular responses to perturbations such as disease, drugs, or gene editing (experiments that change DNA). Depending on their individual genome and other factors, individual cells respond to those perturbations at different speeds, to different degrees or using different cellular mechanisms. Understanding inter-patient and inter-cell heterogeneity is vital in applications in precision medicine. 

Experimentally, single-cell methods such as single-cell RNA-sequencing and single-cell DNA-sequencing, which give information about individual cells, have paved the way for a fine-grained understanding of the heterogeneity of cellular responses to perturbations. However, high noise levels and biases in the data have required the development of specific statistical tools for data analysis and to inform experimental set-up. My research has helped improve understanding of gene regulation in mammalian development and disease, of drug resistance in cancer, and of how to optimise experiments and computational pipelines for high translational impact for drug discovery in industry. I particularly enjoy collaborations with both experimental biologists (e.g. https://www.sanger.ac.uk/news_item/cancer-drug-resistance-causes-and-categories-identified/) and industry (e.g. https://www.cancerresearchhorizons.com/functional-genomics-centre-building-single-cell-crispr-capability). 

My research group focuses on the development and application of statistical and machine learning approaches to single-cell data to improve our understanding of human development, cellular regeneration, cancer and neurodegenerative disease.

PhD and postdoc opportunities: 

Upcoming (October 2025 or January 2026 start): 1 fully funded (at home student fee level) PhD positions in statistical data science for gene editing and single cell methods in  neurodegenerative disease  

Upcoming: Postdoc position in machine learning and statistical analysis for large-scale gene editing to understand immune responses in neurodegenerative disease 

Please get in touch if you are interested in any of these opportunities.