Magdalena is part of the BBSRC London Interdisciplinary Doctoral Programme (LIDo). She is doing a PhD in computational systems biology at Queen Mary University of London, where her focus is on learning and reasoning in cell signalling networks. She is particularly interested in Bayesian networks, logic modelling and automated scientific discovery. Before doing her PhD, she obtained an MSc degree in Biotechnology from the University of Natural Resources and Life Science, Vienna.
Magdalena’s research focuses on causal inference and automated hypothesis generation in signalling networks derived from phosphoproteomics data. Manually mining all the relevant prior knowledge for hypothesis generation is time-consuming, leaving many of the available measurements unexplained and datasets under-analysed. Magdalena is developing probabilistic relational models that describe dependencies between experimental data and prior knowledge while accounting for the uncertainty inherent to most biological data. She aims to improve the explainability of experimental results and automatically hypothesise about aberrant cell signalling in cancer, thereby hastening scientific discovery.