The Digital Health – Machine Learning group at the HPI is looking for an excellent and motivated postdoctoral researcher to join INTERVENE under the supervision of Prof. Christoph Lippert.
The INTERVENE consortium is a 5-year 10 million € EU funded project that aims to develop and test next generation tools for disease prevention, diagnosis and personalized treatment utilizing the first US-European pool of genomic and health data and integrating longitudinal and disease-relevant -omics data into genetic risk scores. The consortium includes 17 closely collaborating partners from 10 countries, with access to data from a total of 1.7 Million genotyped individuals.
The postdoc will 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).
For more information on the position and how to apply, read the full position description PDF.