Thesis title: Augmenting clinical risk predictors through multi-omics
Ola is a computer scientist who is happiest when analysing biomedical data. Her long-term scientific goal is to utilise the knowledge of biotechnology and computing to prevent and treat disorders. To move towards this goal, she focuses on developing computational methods and tools facilitating the analysis of biomedical data.
She completed a BEng in Computer Science at The Silesian University of Technology in Poland in 2015 and since then she has been working as a software developer. In 2016, she started studying toward MSci Biotechnology at the University of Aberdeen. As part of the degree programme, she completed a research placement, where she had an opportunity to use high-throughput/next-generation sequencing technologies to study the evolution and genomic epidemiology underpinning nosocomial Candida infections in Scotland. She joined the Marioni group in 2021 as a precision medicine PhD student, where she works on integrating multi-omic (proteomic, genomic and epigenomic) data into clinical risk prediction tools to prevent or delay the onset of cardiovascular disease.
My research interests lie at the intersection of biology, data science and programming. I am particularly interested in analysing data-intensive sets, where I can build tools directly addressing biological issues.