Research position at the Center for AI in Radiation Oncology (CAIRO) - Medical Data Semantics

The Center for AI in Radiation Oncology (CAIRO) develops data-driven models to improve diagnosis, treatment planning, and outcome prediction in radiation oncology. The CAIRO Data Semantics Taskforce aims to establish a comprehensive data infrastructure that captures medical information in a structured, standardized, and machine-readable format to facilitate training of modern AI solutions. We are seeking to expand the CAIRO Semantics team with a dedicated medical data engineer to support the curation of real-world data sets by harnessing modern LLM solutions, designing and curating semantic data definitions and implementing automated data analytics.

What you can expect

• Support the design and implementation of comprehensive data models and structured information for oncology
• Define and standardize clinical, physical, biological, and technical data using Common Data Elements (CDEs)
• Develop and apply automated systems for extracting, managing, and analyzing unstructured medical data using Natural Language Processing (NLP)
• Harness Large Language Models (LLMs) and agentic AI frameworks for automated data extraction
• Conduct retrospective analyses of clinical data to support ongoing AI and clinical projects within CAIRO, leveraging experience with large clinical databases (e.g., NIS, NSQIP, SEER)
• Act as a bridge between clinical needs and technical execution, translating complex medical workflows into robust data structures
• Be a part of an active research team across disciplines in a leading university hospital

Your Profile

• MD, M.SC, or PhD degree in Health Informatics, Computer Science, Data Science, Medicine, Computational Biology, Biomedical Engineering, or a closely related field
• Demonstrated dual expertise, possessing both a strong technical background in data engineering/data science and medical/clinical know-how
• Proven track record and hands-on experience in data semantics, data definition, and health data structuring
• Strong background in machine learning and deep learning, particularly with NLP and LLMs applied to medical or biological data
• A demonstrable portfolio of software, open-source projects, or AI platforms (e.g., GitHub) is highly desired
• Fluent in English (speaking and writing)
• Experience in clinical oncology workflows or comprehensive cancer centers is highly advantageous

What we offer

• A 2-year position (optional extension) at the level of researcher/research assistant depending on prior experience
• Integration into a multidisciplinary team at the interface of medicine and computer science
• Access to extensive clinical datasets, expert medical annotations, and state-of-the-art computational infrastructure
• Support for conference participation and opportunities for mentoring
• Publication opportunities in leading high-impact clinical, technical, and interdisciplinary journals
• Access to high-performance computing and clinical data environments within Inselspital and the University of Bern

Questions about the job?

Further information will be provided by Sarah Brüningk Write an email Fabio Dennstädt Write an email