The project focusses on human disease identification, utilising AI/machine learning processes followed by experimental validation. The position available will require experimental generation of cell biology data, unbiased evaluation of model predictions, and functional workup of novel disease-associated genes. This includes gene editing, transcriptomics, protein expression studies, and in-vivo validation in model systems.
CRC 1597 "Small Data" brings together highly interdisciplinary, integrating data-driven and knowledge-driven modeling approaches from computer science, mathematics, and statistics/systems modeling, to create comprehensive solutions for tackling small data settings, primarily in biomedicine. Biomedical applications, such as in forensic medicine, gene therapy, nephrology, psychiatry, radiology, or rare diseases, will be instrumental for validating the newly developed methods. All doctoral researchers will become members of our integrated research training group SMART, for fostering interdisciplinary exchange and establishing a shared language between disciplines.
https://www.smalldata-initiative.de/
https://www.smalldata-initiative.de/projects/a04/#open_positions