Are you passionate about uncovering the hidden drivers of cancer evolution? Join the computational cancer biology lab of Martin Schaefer as a postdoctoral researcher, where you'll develop innovative models to identify epigenetic drivers of late stage carcinogenesis.
Cancer is driven by alterations on all molecular levels. While our knowledge about the contribution of point mutations to the phenotypic hallmarks of cancer has advanced substantially over the last decade, we still need to solve the puzzle of how the numerous quantitative changes (eg epigenetic or transcriptional) are related to cancer initiation and progression. We are looking for a computational postdoc to develop models of selection to identify epigenetic drivers of carcinogenesis.
Your work will contribute to solving one of the most critical puzzles in cancer biology—linking quantitative molecular changes to cancer initiation and progression - by analyzing cutting-edge data types such as WGBS, EM-seq, and ONT sequencing. Your role will involve investigating key questions such as:
The successful candidate will work together with other members of the lab as well as with wet lab and clinical collaborators.
Candidates should hold a PhD in bioinformatics/computational biology, biostatistics, computer science or a related field. They should have expertise in statistics, programming, and the analysis of cancer omics data. Knowledge of other data science techniques in particular machine learning and being familiar with concepts of tumor evolution are a plus.