MSc Thesis: Combinatorial Optimization for Radiation Therapy Patient Scheduling

RaySearch develops innovative software solutions to improve cancer care. Over 1200 clinics in more than 54 countries use RaySearch software to improve treatments and quality of life for patients. RaySearch was founded in 2000 and is listed on Nasdaq Stockholm. The headquarters is located in Stockholm, with subsidiaries in the US, Europe, Asia and Australia & New Zealand. Today we are more than 485 employees with a common vision of improving cancer care with innovative software. Our great staff is crucial for our success and we offer a fantastic working environment in modern offices, flexibility and good opportunities for development. We believe in equal opportunities, value diversity and work actively to prevent discrimination. 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. Your profile 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.