• PhD, preferably in Medical Informatics or Bioinformatics
• Strong knowledge and experience with ML data analysis methods and their data requirements
• Demonstrated experience with sensitive individual-level human biomedical, clinical or omics datasets
• Strong expertise in biomedical metadata, data models, ontologies, clinical/data dictionaries and FAIR principles, including preparation of datasets for repository deposition
• Understanding of secure federated data analysis and data governance

The TBI group at the University Hospital Tübingen operates at the intersection of medical informatics and bioinformatics. As part of the Department for Information Technology and Applied Medical Informatics (DITAMI) and by its close connection to the Interfaculty Institute for Bioinformatics and Medical Informatics (IBMI) at the University of Tübingen the TBI concentrates interdisciplinary expertise for successful translational research in the Digital Life Sciences and the comprehensive and widespread education of qualified researchers. To address the clinical and molecular complexity of COVID-19 and PCS/Long COVID, the German National Pandemic Cohort Network (NAPKON) has established one of the most comprehensice research infrastructures globally (https://napkon.de). However, a big part of the data still needs to be harmonized and annotated semantically. We aim to establish a curated, FAIR-compliant corpus of NAPKON multi-omics and clinical data that can be used to develop, apply and validate ML and AI methods and models for COVID-19 or PCS research. Especially, we will deposit selected data into the secure processing enviroment of the German Human Genome-Phenome-Archive (GHGA). This is a DFG-funded project in cooperation with other universities.