Available Positions

Postdoc in Statistical Human Genetics and Machine Learning

Prof. Christoph Lippert's lab at Hasso Plattner Institute is recruiting a postdoc to work on the development and application of next generation risk prediction methods. This will involve learning interpretable representations from high-dimensional electronic health record data and using these representations to improve the performance of integrative risk scores. On the genetics side, the postdoc will leverage functional sequence annotations to prioritize causal genetic variants and improve interpretability and generalizability of genetic risk scores.  We are primarily looking for candidates with a background in statistics, machine learning or related data science. The ideal candidate would also have experience in genetic prediction methods (e.g., polygenic risk scores), genome-wide association studies and sequencing data, or experience working with imaging or health-record data (e.g., UK Biobank).