Location: Department of Oncology, Odense University Hospital (OUH) & University of Southern Denmark (SDU)
Duration: 3 years
We are seeking a highly motivated PhD candidate to join a collaborative research initiative at the intersection of the AIM@cancer foundational AI project and the DAHANCA FORWARD project. The position is formally based at the Department of Oncology, Odense University Hospital, and affiliated with the University of Southern Denmark.

AIM@cancer is a newly founded Novo Nordic project focusing on developing a foundational model for radiotherapy trained on high-quality Danish data, and the DAHANCA FORWARD project has collected more than 16.000 head and neck cancer treatment plans. The PhD project combines the two projects, utilising extensive data on one of the world's most powerful supercomputers, Gefion.

The successful candidate will contribute to the development of AI methods to enhance radiotherapy for patients with head and neck cancer, thereby potentially reducing treatment-related adverse effects and improving the quality of life for these patients. The project will focus on transforming large-scale clinical data into automated clinical treatment plans and patient outcome predictions, utilising machine learning of medical images and unstructured text from patient journals.

Why apply? You will work with exceptional data, serious computing power, and a supportive, cross-disciplinary team of clinicians, physicists, and data scientists, giving you a rare chance to translate cutting-edge AI directly into clinical impact.


Research focus
The PhD project will encompass four main subprojects:

1. Automated data collection from medical image archives – developing robust pipelines for large-scale imaging and radiotherapy data.
2. Outlier detection and automated data cleaning – ensuring data quality and reliability in multi-centre studies.
3. Automated AI treatment planning annotation – integrating AI to support segmentation (the process of outlining tumours and healthy organs in medical images) and treatment planning workflows.
4. AI-based dose prediction – modelling and predicting radiotherapy dose distributions using advanced AI methods.

AI and radiotherapy research in Odense
At the OUH Oncology department, we have built a strong environment for AI in radiotherapy. We have developed DcmCollab, a national radiotherapy database used as AI hub for segmentation and automated data workflows, which serves as a cornerstone for current and future AI research.

Our group has a strong track record in bringing AI research into clinical practice, supporting patients with improved treatment quality while streamlining workflows for healthcare professionals.

The radiotherapy research group in Odense consists of:

• Two professors in medical physics
• Three Associate Professors
• Two Postdoctoral Researchers
• Five PhD Students
• Two Data Engineers
• Ten Medical Physicists involved in research activities

This strong, interdisciplinary team provides an ideal foundation for translating AI innovations into patient benefit.


Qualifications

• Master’s degree (or equivalent) in medical physics, computer science, data science, biomedical engineering, applied mathematics, or a related field.
• Strong programming skills (e.g. Python, R, MATLAB, or similar).
• Experience with medical imaging, radiotherapy, or AI/machine learning is an advantage but not a requirement.
• A genuine interest in understanding clinical practice, including how treatments are delivered and how AI can support patient care.
• Excellent communication skills in English, both written and spoken.
• Ability to work both independently and in a collaborative research environment.

We offer
The position is part of a flexible and flat organisational environment that encourages initiatives and collaboration. While we value flexibility, we expect the candidate to be physically present in Odense approximately four days per week to foster close collaboration. Further, we offer:

• A dynamic and interdisciplinary research environment bridging clinic and academia.
• Access to state-of-the-art clinical data and high-performance computing resources.
• Close collaboration with national and international partners through AIM@cancer and the DAHANCA networks.
• Opportunity to contribute to cutting-edge research that may directly impact future cancer treatment.

Application
Applications must include:

• A motivated cover letter, please use your own words and let AI help you with other tasks.
• Curriculum Vitae (CV).
• Academic transcripts and diplomas.
• Contact information for at least two references.

The selected candidate will, together with the supervisors, prepare the final PhD project description as part of the enrolment process at the University of Southern Denmark (SDU). Formal enrolment will take place once the project description has been approved by the PhD School at SDU.


Application deadline: 31 October 2025
Expected start date: January 2026

Interviews will be held shortly after the application deadline.

For further information, please contact:
Christian Rønn Hansen, Associate Professor, Department of Oncology, OUH. Email: Christian.roenn@rsyd.dk