Computational Genomics and Systems Genetics

How does our genetic background shape phenotypic traits or cause cancer? How are genetic and environmental factors integrated at different molecular layers, and how variable are molecular states between individual cells?

We use statistical inference and machine learning as our main tools to address these scientific questions. Growing sample sizes and technological advances demand novel analytical strategies and tools that scale to datasets with millions of observations and account for spatial and temporal dependencies. We develop foundational methods in statistics and machine learning, including efficient parameter inference in models to probe genetic associations and methods for dimensionality reduction.

Find out more about our lab at https://steglelab.org/

We are always looking for new talent to strengthen our team!

To apply for a postdoctoral position or PhD position in our group, please refer to the DKFZ Postdoctoral Fellowship and the DKFZ International PhD Programme. 
If you do not apply through one of the specific openings mentioned above, feel free to send your CV, a letter of motivation and ideally 2 references in a single pdf directly to Oliver Stegle. 

We are also pleased to offer opportunities for your BSc or MSc thesis or an internship in our lab. If you are interested, please contact us with a CV and a motivation letter tailored to our lab interests.