MSc Thesis: Optimization & Control Strategies in Online Adaptive Radiation Therapy

Join us in advancing online adaptive radiotherapy by developing optimization strategies that improve treatment accuracy and compensate for errors throughout the treatment course.

Project Description

Online adaptive radiotherapy (OART) uses images acquired immediately before or during a treatment fraction to adapt the treatment plan to the patient’s anatomy of the day. In conventional radiotherapy, one plan is typically created from a planning image and delivered in fractions over the course of multiple weeks, with limited adaptation if substantial anatomical changes occur. OART can therefore improve target coverage and reduce dose to organs at risk. However, repeated daily re-optimization raises the question of how each adapted plan should contribute to the intended dose over the full course of treatment, and how errors arising from automated workflows should be mitigated along the way.

This thesis project will investigate optimization strategies that account for previous errors and the dose already delivered when reoptimizing each daily plan. The aim is to compare methods for steering the accumulated dose toward the treatment objectives especially considering compensation for over- or underdosage resulting from unexpected errors earlier in the treatment.

To be eligible for this position, you are a master's student within applied/computational mathematics, engineering physics, or a related field, and have excelled in your studies. You have an interest in software development and contributing to our mission. Experience with mathematical optimization, dynamical systems, and/or control theory is an advantage. Fluency in English is required.

Application

Please apply to the position through the link below. Selection and interviews will be ongoing. We do not accept applications by e-mail.

Application Link.