Cell imaging-based diagnostic platform for patients with rheumatic diseases We are looking for a motivated student who is skilled in machine learning and algorithm development to explore our large multi-fluorescence imaging datasets at the single cell level, to build and validate a computational workflow for automated image analysis.
Our aim is to create a diagnostic platform based on single-cell imaging to characterize the functional stage of synovial fibroblasts (SF) from patients with rheumatic diseases and predict an efficient, tailored, in vitro tested treatment as part of our precision medicine approach to improve the course of rheumatic diseases.
We are currently looking for Master’s students in the field of Bioinformatics for the topic of
Nucleosome footprints in cell-free DNA sequencing data Cell-free DNA (cfDNA) is released by dying cells into the surrounding tissues and also to the bloodstream. As nucleosomes protect DNA from degradation, plasma cfDNA carries information about the nucleosome organization in the cells of origin. Different characteristics of cfDNA are increasingly being used in the diagnostics of genetic diseases and the monitoring of cancer.