Our institute is a leader in the bioin­for­matic analysis of genetic high-throughput data, parti­cu­larly in the develo­pment of biomarker signa­tures and advanced approaches of machine learning for perso­na­lized and systems medicine.
Within different DFG or BMBF funded Colla­bo­rative Reserach Projects focused on for instance on pancreatic cancer, colorectal cancer, we pioneer the develo­pment of innovative computer-assisted methods in bioin­for­matics and artificial intel­li­gence. This includes the analysis and integration of various OMICs data, including genomics, transcrip­tomics, and spatial transcrip­tomics.PhD Topics:
Within these research groups, we offer ambitious young scien­tists the oppor­tunity to work at the forefront of research in Medical Bioin­for­matics. Possible topics for doctoral theses are deeply rooted in the analysis of complex datasets and the develo­pment of methods essential for progress in the treatment of pancreatic and colorectal cancer.

Furthermore in context of our new project GöNoMix, we develop compu­ta­tional methods to recon­s­truct gene regulatory networks (GRNs) in emerging model organisms. We integrate ATAC-seq, RNA-seq and TFBS analyses, model WNT signaling, improve machine-learning methods and create tools for cross-species compa­risons.

We are looking for PhD candi­dates interested in statis­tical data analysis, machine learning methods, gene regulation, bioin­for­matics, and integrative omics approaches.