Join the Center for AI in Radiation Oncology (CAIRO)
The Center for AI in Radiation Oncology (CAIRO) is dedicated to developing data-driven models aimed at enhancing diagnosis, treatment planning, and outcome prediction in radiation oncology. Our Data Semantics Taskforce is focused on establishing a robust data infrastructure that captures medical information in a structured, standardized, and machine-readable format, facilitating the training of modern AI solutions. We are looking to expand the CAIRO Semantics team with a dedicated Medical Data Engineer to support the curation of real-world data sets by harnessing advanced Large Language Model (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 utilizing Natural Language Processing (NLP).
- Leverage 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, utilizing 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.
- Collaborate within an active research team across disciplines at one of the leading university hospitals.
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 with a strong technical background in data engineering/data science and medical/clinical knowledge.
- Proven track record and hands-on experience in data semantics, data definition, and health data structuring.
- Strong foundation in machine learning and deep learning, particularly with NLP and LLMs applied to medical or biological data.
- A demonstrable portfolio of software projects or AI platforms (e.g., GitHub) is highly preferred.
- Fluent in English (both speaking and writing).
- Experience in clinical oncology workflows or comprehensive cancer centers is highly advantageous.
What We Offer
- A 2-year position (with optional extension) at the level of researcher/research assistant, based on prior experience.
- Integration into a multidisciplinary team at the intersection of medicine and computer science.
- Access to extensive clinical datasets, expert medical annotations, and cutting-edge 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.
Apply online using the form below. Only applications matching the job profile will be considered.
Questions about the Job?
For further information, please contact:
Sarah Brüningk
sarah.brueningk@unibe.ch
Fabio Dennstädt
fabio.dennstaedt@insel.ch