The Fraunhofer Institute for Translational Medicine and Pharmacology ITMP investigates and develops innovative ways of early detection, diagnosis, and treatment of diseases resulting from impaired function of the immune system.
At ScreeningPort (SP), the Hamburg site of the Fraunhofer ITMP, we conduct experimental and informatics-based research across the spectrum of drug discovery and development. An important aspect of our work is biomedical data science, wherein ITMP-SP's goal is to provide solutions for FAIR handling and analysis of research data. We design infrastructure and software tools that enable research and industry to evaluate concepts of digitized health research and their commercial applications through open research platforms and test environments. One of your assignments will revolve around implementing a FAIR data strategy in the Fraunhofer coordinated »IDERHA«, a public private project, which is funded under the Innovative Health Initiative (IHI). IDERHA addresses the key barriers that prevent appropriate access, sharing, use, and re-use of lung cancer data, thus enabling improved recommendations for regulatory and HTA decision-making in integrated health research to improve care and to better meet the needs of patients and healthcare professionals. You will work with teams to develop and extend standards for semantic interpretation, data quality, ethics, and transferability in order to ensure the overall harmonization of heterogeneous data sources and the wider re-use of health data.
What you will do
- Create and optimize ETL processes: prepare, harmonize and annotate scientific and clinical data from a wide variety of internal and external sources
- Implement FAIR guidelines and further develop scientific research data management within Fraunhofer and among our cooperation partners
- Participate in national and international collaborations (e.g. projects of the Innovative Health Initiative (IHI), specifically IDERHA, the European platform for clinical data connectivity and regulatory health assessments)
- Prepare data management plans
- Identify and implement appropriate software tools to simplify our workflows and data analysis processes
- Develop the Fraunhofer range of services for digitized medicine (e.g. Fraunhofer Edge Cloud)
What you bring to the table
- Bachelor's or Master's degree in life sciences, bioinformatics or related natural sciences
- Ideally, but not required: a qualification in chemoinformatics
- Experience in scientific data management / data engineering, the creation of data management plans and the implementation of FAIR guidelines
- Routine use of (meta)data standards and ontologies
- Solid understanding of scientific databases and data repositories
- Creative approach to the design and evolution of data architectures
- Knowledge of SQL/NoSQL databases
- Experience in working with in vivo data or personal data in the context of pharmaceutical drug discovery
- Advantageous: background in Python, R, statistics, KNIME, JSON-LD, APIs: REST, SOAP, web scraping, Fiji, OMERO or knowledge graphs as well as experience with agile working methods (e.g. Scrum)
- Excellent team and communication skills with a high degree of self-organization
- The position requires fluency in English, additional German language skills are a plus
What you can expect
- A role in a vibrant and exciting professional environment nurtured by our open culture and community spirit
- A diverse, international workforce with a dynamic atmosphere that encourages creativity, innovation and teamwork
- The opportunity to collaborate with a large network of data scientists from academia, pharma and health technology
The weekly working time is 39 hours. The position is initially limited to 2 years and can also be filled in part-time. We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Appointment, remuneration and social security benefits based on the public-sector collective wage agreement (TVöD). Additionally Fraunhofer may grant performance-based variable remuneration components.
With its focus on developing key technologies that are vital for the future and enabl