YOUR FUTURE IN DETAIL

The Institute for Biomedical Informatics (BI-K), in collaboration with the Medical Data Integration Center (MeDIC), is seeking a Data Engineer and Researcher. The successful candidate will be involved in innovative, interdisciplinary research projects addressing key challenges in the biomedical field.
This role involves data curation, integration, analysis, and improving data quality to support reliable biomedical research, while also exploring and applying artificial intelligence (AI) and large language models (LLMs) to automate and enhance these efforts. This dual focus offers a unique opportunity to contribute to both the technical infrastructure and the intelligent systems that drive biomedical data science forward.
You will have the opportunity to work closely with outstanding experts in medicine and computer science with medical data in a real health setting. Besides excellent technical and research skills, you will require communication skills to participate in national and international networks, such as EOSC, NFDIs and present research outcomes.
You will also have an option to pursue a PhD in computer science, with a specific focus on LLM and agentic AI.
The successful candidate will work together with clinics to develop and implement strategies to improve data driven decision making in their daily practice and research.
Applications from female candidates are expressly welcome and will be given priority in the event of equal suitability, competence and professional performance. People with disabilities are welcome to apply and will be treated preferentially in the event of equal suitability and qualification. The position is suitable for staffing with part-time employees.

• Collaborate with clinicians, data stewards, and informaticians to understand data semantics in the clinical context
• Integrate multilayered data of multiple data sources to support clinics in their digitalization
• Collaborate with our Medical Data Integration Center to design, implement, and maintain ETL pipelines for ingesting, transforming, and harmonizing clinical data from EHRs and related systems
• Research, develop and validate machine learning models and LLM-based tools to enhance clinical data quality, anomaly detection, and automated data cleaning
• Apply biomedical metadata standards to ensure data quality, interoperability, and integration
• Compile, validate, and benchmark datasets for evaluating LLMs in key biomedical use cases such as generating patient summaries, focusing on specific rare diseases
• Interoperable, Reusable principles, Open Science standards, and robust software design methodologies
• Engage in interdisciplinary collaborations to develop innovative LLM-driven solutions for biomedical data challenges and knowledge extraction