PhD Student in Statistical Genetics and Machine Learning | PhD Student (m/w/d)

Job Summary

This PhD position focuses on developing and applying cutting-edge computational, statistical, and Machine Learning (ML) methods for analyzing large-scale genomic, clinical, and phenotypic datasets, including Phenome-Wide Association Studies (PheWAS) and precision medicine applications. The successful candidate will analyze high-dimensional data from biobanks and clinical systems, contributing to the creation of next-generation molecular atlases for chronic diseases. The role requires a Master’s degree in bioinformatics, computer science, statistics, or a related quantitative field, along with a solid foundation in statistics, ML (e.g., supervised learning, regression modeling), and strong programming skills in Python and/or R. This is an attractive opportunity to conduct high-impact research within the internationally recognized Institute of Clinical Molecular Biology (IKMB) at Kiel University, collaborating closely with the 'Precision Medicine in Chronic Inflammation' (PMI) Excellence Cluster and utilizing state-of-the-art technologies and biobank-scale datasets.