PhD Statistical Genetics / Machine Learning

The Biomedical Informatics and Genetic Phenotype Redefinition Research Group at the Institute of Clinical Molecular Biology (IKMB), Kiel University (CAU) and the University Medical Center Schleswig-Holstein (UKSH), is seeking a PhD student with a strong background in statistics, machine learning (ML)/artificial intelligence (AI), or bioinformatics.

Our group develops novel computational and statistical methods for the analysis of large-scale genomic, clinical, and phenotypic data, including phenome-wide association studies (PheWAS), statistical genetics, and precision medicine applications. This includes the development of scalable software tools and pipelines, potentially leveraging GPU/FPGA accelerators. Our aim is to build next-generation molecular atlases for chronic diseases and to improve patient stratification for personalized prevention, diagnosis, and therapy.

We collaborate closely with the Department of Computer Science (CAU), the Comprehensive Center for Inflammation Medicine (CCIM), and the Competence Centre for Genomic Analysis (CCGA). As part of the Cluster of Excellence "Precision Medicine in Chronic Inflammation" (PMI), our group has published more than 100 peer-reviewed publications, including numerous high-impact articles in statistical genetics, biomedical data science, bioinformatics and genomics.

• Master's degree in bioinformatics, computer science, statistics, mathematics, or a closely related field with a strong quantitative focus on these fields
• Solid foundation in statistics and/or machine learning, e.g., supervised learning, regression modeling, model evaluation, or high-dimensional data analysis
• Good programming skills in Python and/or R; experience with Linux/HPC environments is an advantage
• Experience with genomic data analysis, high-performance computing, GPU programming, or software development is a plus
• Excellent English communication skills and strong ability to work collaboratively.

• Competitive salary according to TV-L E13 (75%), subject to collective bargaining regulations
• An interdisciplinary, data-rich research environment with access to biobank-scale genomic datasets and state-of-the-art technologies
• Close collaboration with computational experts, core facilities (Genomics and Bioinformatics), and partners within the PMI Excellence Cluster
• Opportunities for conference participation, workshops, and advanced training
• Flexible working hours and support in balancing work and family life

What you can expect:

• Develop and apply computational, statistical, and ML-based methods for large-scale genomic and phenotypic datasets (e.g., PheWAS, statistical genetics, prediction models)
• Analyze high-dimensional data from biobanks and clinical information systems
• Contribute to teaching activities in the Medical Life Sciences program
• Complete your PhD at Kiel University (CAU), with the doctoral degree awarded either through the Faculty of Engineering or the Faculty of Mathematics and Natural Sciences, depending on your academic background and preference