by Raphael Bednarsky
Photo by: CeMM/Laura Alvarez
Nowadays, foundational medical research is unimaginable without computational methods, and the development of those enables an understanding of disease and treatments like never before. Biological entities are among the most complex systems we know of, and high throughput laboratory method progress in recent years provides immense and ever-growing amounts of data. Tissues and cells are now described from multiple perspectives at once, ranging from their gene expression and metabolic state to morphological features and spatial arrangement in tissues. This challenging data needs computational expertise in fields such as deep learning to exploit its maximum potential. We need computational methods to understand and predict cell behaviour in realistic contexts. This will allow us to predict the success of a therapy for each individual patient, and to adapt it accordingly. If successful, our work can thus have a direct positive impact on millions of lives worldwide.
I am doing my Ph.D. working as a biomedical data scientist at the Institute for Artificial Intelligence of Med Uni Vienna, under the supervision of the head of the institute, Christoph Bock. Here, we combine high dimensional data from cutting-edge laboratory methods with innovative computational approaches. More specifically, I am developing an interpretable deep learning method to understand how cancer avoids being killed by immune cells. We directly profit from our presence at Med Uni Vienna, using patient samples in many of our projects and collaborating with clinicians in translational research. Being surrounded by both biologists and computational scientists helps me grow and contribute to medical advancement, aiming for maximum impact on peoples’ lives.
Cancer is currently the leading cause of death worldwide (WHO, 2022) and with my work I hope to find a way to identify the Achilles heel of different types of cancer cells so that in the future we know how to teach our immune system to kill them.
If working in this environment also sounds interesting to you: The institute is growing, and we are looking for Post Docs and Junior Group Leaders! Visit our website to find out more about current career opportunities.