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

Please submit a single PDF containing your curriculum vitae, a cover letter outlining your motivation and preferred project (1–2 pages), academic transcripts (Bachelor's and Master's), and contact information for two references or relevant letters of recommendation with corresponding contact details