The Faculty of Medicine of the University of Bern and Inselspital, Bern University Hospital invite applications for an Assistant Professorship in Clinical Cancer Informatics, funded by the Werner and Hedy Berger-Janser Foundation.

This endowed professorship is embedded within the University Comprehensive Cancer Center Inselspital (UCI) and jointly affiliated with the Department of Medical Oncology and the Department of Radiation Oncology.

The position aims to strengthen data-driven, patient-centered cancer research and to advance the integration of clinical data, artificial intelligence, and precision oncology. It is designed to serve as a key interface between clinical practice and data science, enabling the transformation of real-world data into clinically meaningful insights.

Scientific Environment

Bern offers a highly collaborative and rapidly evolving ecosystem in digital medicine, including:

- Access to large-scale clinical datasets and real-world patient data

- Established infrastructures in data science and clinical research

- Strong interdisciplinary collaboration across clinical departments, biomedical research, and digital medicine

- Integration within national and international research networks The successful candidate will benefit from close collaboration with the Department of Clinical Research (DCR), the Department of Digital Medicine (DDM), and the Department for BioMedical Research (DBMR), the ARTORG Center for Biomedical Engineering Research and the Center for AI in Radiation Oncology (CAIRO).

Start date: 2027

Workload: 100% (job-sharing models welcome)

Duration: 4 years (an extension by a further two years may be considered following an evaluation before the end of the four-year term; the evaluation will also review long-term funding and the potential establishment of a structural professorship)

Employment Relationship

fixed-term
Description
Your Responsibilities

- Develop and lead an innovative research program in clinical cancer informatics

- Advancement of standardized terminologies, interoperabilities and mapping strategies to harmonize heterogeneous data sources

- Integrate heterogeneous clinical data sources and develop advanced analytical approaches

- Contribute to the development of AI-based decision-support tools in radiation oncology and medical oncology

- Strengthen interdisciplinary collaboration between clinical and computational disciplines

- Acquire competitive third-party funding

- Contribute to undergraduate and graduate teaching and supervise early-career researchers

- Actively participate in the strategic development of digital medicine at the Faculty of Medicine
Requirements
Your Profile

We are seeking a highly motivated and collaborative individual with:

- A medical degree (MD or equivalent) or PhD with strong clinical insight

- Excellent research achievements in clinical informatics, data interoperability and standardization, data science, or a related field

- Experience with real-world medical data, AI, or computational methods in healthcare

- A strong interest in translational and interdisciplinary research

- Demonstrated ability (or strong potential) to lead research teams

- Excellent communication skills and ability to work across disciplines

- Fluency in English; German skills or willingness to acquire them
We offer
- A unique opportunity to shape a highly innovative and rapidly developing field

- Access to excellent clinical and research infrastructure

- Integration into a dynamic and collaborative academic environment

- Dedicated funding through the endowed professorship

- Support for career development and long-term perspectives (following an evaluation before the end of the four-year term, an extension by a further two years may be considered; long-term funding and the potential establishment of a structural professorship will also be reviewed.)

Self-conception

The University of Bern is committed to increasing the proportion of women in academic leadership positions and strongly encourages applications from female candidates and individuals from underrepresented groups. Applications under job-sharing models are welcome; interested parties are requested to submit a corresponding concept. Flexible working arrangements are supported. ( https://www.vereinbarkeit.unibe.ch/index_eng.html )

In your application, please refer to myScience and reference JobID 70476.