Online adaptive radiotherapy is a technique where the treatment is continuously adapted to the changing patient anatomy. Such a treatment allows for a more precise delivery of the ionizing radiation, leading to less radiation induced side effects and opening the potential for further dose escalation.

A crucial step in this process is the segmentation of the tumour and healthy tissues on daily acquired medical images (MRI or CT). Manual segmentation however is time consuming, prone to variation between clinicians and a logistic burden due to specialist staff requirements. As such, segmentation is typically considered the weakest link in radiotherapy. Therefore, there is a clear clinical need for a fast, comprehensive automated segmentation workflow.
Artificial intelligence, and in particular deep convolutional neural networks, have shown potential of automated segmentation; however, in practice the clinical use is very limited. One of the reasons for this is that the obligatory manual verification of auto-segmentation is time consuming and it is hard for clinicians to recognize quickly where a segmentation requires correction.

The aim of this project is to develop AI tools to study the quality of (automated) segmentations in online adaptive radiotherapy. These tools should lead to a framework that allows clinicians to automatically recognize those regions of a segmentation that likely require clinically relevant corrections. In this way, we expect efficiency and quality of treatments to improve. This is not just fundamental research, at the end of the project the tools will be implemented in our clinical practice. Clinical indications involved are MR-guided online adaptive radiotherapy for rectal cancer and CT-guided adaptive photon and proton therapy for head and neck cancer.

Applications are invited for a 4-year full-time PhD position in a joint project between the departments of radiation oncology of the Netherlands Cancer Institute and the University Medical Center Groningen. You will collaborate closely with other researchers both in radiotherapy as in computer vision, as well as with medical physicists, radiation oncologists and radiotherapy technicians. 

We are looking for a highly motivated and enthusiastic PhD student with a strong affinity for radiotherapy and AI. The candidate should have a master’s degree in physics, mathematics, computer science or related. A background in either AI or radiation physics as part of the master program is recommended. Strong communication skills are required in this multidisciplinary project. While the position is primarily in Amsterdam, part of the project will be performed in Groningen.

Fixed-term contract: 4 years.

Your temporary employment will be for a period of 4 years. The gross salary per month for our PhD will range from € 2.972,- to a maximum of € 3.620,- according to the standard PhD scales. The terms of employment will be in accordance with the Collective Labor Agreement for Hospitals. In addition you will receive a fixed end-of-year bonus (8,33%) and you will receive 8,33% holiday pay. 

Your travel expenses will be reimbursed at € 0,19 per km. Free parking at the Antoni van Leeuwenhoek is also part of the package. Personnel is stimulated to use public transport and bicycle and therefore we offer an interesting arrangement for bikers and/or discount on the NS-business card. 

For more information in regards to the secondary conditions please visit our website: https://www.nki.nl/careers-study/how-to-apply/.