PhD Student – AI-based Assessment of Radiotherapy Delineation Quality

Accurate delineation of the tumor is essential in radiotherapy. However this task is challenging and substantial variation between clinical experts is observed. For some tumors AI based automated segmentation has shown to be able to accurately delineate the tumor on medical images. For retroperitoneal sarcoma (RPS) a rare cancer the quality of these approaches is challenged by the large variations in interpretation of the medical images in clinical practice by the radiation this project we intend to tackle this issue for RPS by combining AI based auto-segmentation methods with clinical outcome data. Our goal is to define the delineation that results in the best clinical outcome.

As a PhD student you will select tune and train the algorithms required for this problem. Furthermore you will develop the scientific methodology to establish the clinical usefulness of the results. This requires a thorough understanding of both the clinical problem and of state-of-the-art AI approaches for medical image segmentation. Moreover you are responsible to 1) translate these results into tools usable by radiation oncologists and 2) to establish the clinical value. As such your project will extend from state-of-the art AI segmentation towards day-to-day clinical routine.

You will work in a multidisciplinary environment closely collaborating with radiation oncologists medical physicists imaging experts and data scientists. The project is a collaboration between NKI and Radboudumc Nijmegen. The primary location is NKI but you will spend time at both institutions.

We are looking for a highly motivated PhD candidate with a strong scientific interest in radiation oncology and AI and an eagerness and skills to succeed both in technical research and clinical application. Successful candidates typically bring a combination of the following:

• A Masters degree in (bio)medical sciences technical medicine physics mathematics biomedical engineering computer science AI or a related field;

• Strong analytical and problem-solving skills; ability to handle complex datasets;

• Experience or strong interest in the application of AI in the context of medical imaging and radiation oncology;

• Ability to combine insights from data science and routine clinical practice;

• Curiosity creativity and the ambition to develop independent research skills;

• Good communication and teamwork skills in a multidisciplinary environment;

• Excellent command of English; Dutch language skills are an advantage but not required;

• A well-balanced mix of analytical strength creative thinking and a pragmatic mindset.

Your development opportunities and employment conditions

The basis for your employment conditions is in accordance with the CLA Hospitals. You will receive from us:

• A contract for a period of four years for 36 hours per week;

• A gross monthly salary between 3.665- and 4.450- based on a 36-hour working week in line with the OIO scale and depending on your experience;

• 144 holiday hours and 57 hours of Personal Life Budget with full-time employment;

• Annual holiday pay of 8.33% and a fixed end-of-year bonus of 8.33%;

• A travel allowance of 0.23 per km;

• Free parking at the Netherlands Cancer Institute. And with our bicycle plan and discount on public transport we also make it attractive for you to leave the car at home;

• An active PhD council;

• Opportunity to exercise during working hours at our Fit Boutiqs.

• A challenging and ambitious PhD project on advanced clinical application of AI in radiation oncology.

• Supervision and mentorship by leading experts in the field.

• A stimulating collaborative and international research environment at some of Europes top cancer and medical AI centers.

Interested

Apply now by using the apply/solliciteer button at the top of the page. Applications sent directly by e-mail will not be processed. Please attach your motivation letter CV and contact details of two references to the application form. Make sure to include your reference information together with your application documents as there is no option to submit them separately.

This vacancy is open for applications until 18 January 2026.

We plan to hold the first interviews on 30 January 2026.

For further information about the position please contact Tomas Janssen .