MSc Thesis: Combinatorial Optimization for Radiation Therapy Patient Scheduling

About half of all people will be diagnosed with cancer during their lifetime. Nearly a third of those will receive radiotherapy, making the efficient use of healthcare resources of the utmost importance. Yet in many clinics, creating patient schedules is still done manually.

Project Description

Radiotherapy scheduling is a highly complex optimization problem. Schedules must satisfy numerous clinical and technical constraints while achieving clinical and operational objectives such as minimizing patient waiting times, overall treatment time, and so on.

At RaySearch, we are developing a new scheduling system capable of automatically generating high-quality treatment schedules within seconds. Our current scheduling engine, while effective, has limitations in flexibility and ease of use. We want to investigate if a simpler, more general solution can solve the problem.

Your main tasks

Reviewing the state-of-the-art in scheduling optimization.Designing and implementing a general, global and future-proof optimization algorithm for radiotherapy appointment scheduling.Comparing the proposed approach against our existing scheduling method in terms of solution quality, computational performance, and scalability.Validating the algorithm using realistic clinical scheduling scenarios.

We are looking for someone who thrives in the details. Someone who has an appreciation for mathematics and its real-world applications. Someone who can work independently, while still considering feedback from a team. And, ideally, someone who finds scheduling interesting.

More Specifically, We Are Looking For Someone Who Is/has

Master student in Computer Science, Applied Mathematics, Operations Research, Engineering Physics, or similar fields, who has excelled in their studies.Strong interest in optimization and algorithm design.Experience with mathematical modeling, combinatorial optimization or scheduling problems is a plus.Programming experience in C++, Python or similar languages.

It’s an advantage, but not required, if you also have experience using C# or git.

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.