• You contribute to the development of our translational drug response profiling (DRP) platform for functional screening of cancer patient samples.
• In doing so, you build scalable bioimage analysis workflows for clinical applications using deep learning, in close collaboration with the BioVisionCenter at UZH.
• You design and implement sustainable data pipelines and data mappings (FHIR, OMOP) to enable federated international collaboration in pediatric oncology.
• You integrate functional and clinical data using language models to support and automate tumor board preparation and documentation.
• As part of a dynamic team of biologists, clinicians, and data scientists, you work within an international program in pediatric precision oncology at the interface of research and clinical translation.

• Master's degree in Bioinformatics, Computational Biology, Data Science or a related field
• Previous experience with data modeling, building data pipelines, machine learning and application of large language models
• Solid understanding of molecular and cancer biology
• Strong knowledge in high-level programming languages including Python, R and SQL
• Technical proficiency with HPC environments, training of neural networks (PyTorch) and DevOps practices (version control, containerization, CI/CD); Additional experience with modern web technologies (FastAPI, React, etc.) is a plus
• Professional fluency in English (written and spoken), German skills are a strong advantage

Fabio Steffen
Wissenschaftlicher Projektleiter
+41 44 249 79 03