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Master’s Thesis, Optimization 2

We offer a master’s thesis position within the research department at our head office in central Stockholm. The aim of the thesis project is to develop software algorithms for optimal fulfillment of treatment planning goals as specified by clinicians. Key tasks include formulation of clinical goals into mathematical functions that are amenable to optimization, implementation of such functions in a C++ environment, and subsequent evaluation and analysis in RayStation: our treatment planning platform that is used at hundreds of clinics worldwide. 

Background and purpose

A majority of cancer patients undergo radiation therapy as part of their treatment. Optimization is used to shape the distribution of the therapeutic dose in a way that minimizes the risk for adverse effects while ensuring that the disease is cured. The optimization of a treatment plan relies on a mathematical description of the purpose of the treatment on the form of optimization functions that quantify the goal fulfillment for the tumor and adjacent healthy organs. 

The optimization functions that are used in today’s clinical practice are generally chosen due to mathematical well-behavedness rather than clinical meaningfulness. A clear drawback of this disconnect between the mathematical description of the optimization and the doctor’s prescription is that a considerable amount of parameter tuning can be necessary before an optimized plan is accepted for treatment. The purpose of the thesis project is to develop formulations and algorithms that decrease the gap between the mathematical and the clinical plan evaluation criteria. Ultimately, the goal is to find treatment plans that maximize the level of clinical goal fulfillment. The tools developed within the project have the potential to provide more time-effective or even automated planning as well as improved treatment quality.


About the department

The responsibility of the research department is to take brilliant ideas on how to advance radiotherapy planning and turn them into software prototypes. Promising prototypes are then further refined by the development department to be parts of our advanced software for radiotherapy planning. The research department is also involved in several research collaborations with clinical cancer centers all over the world.


Education and Experience 

  • This master’s thesis project is suitable for degrees in applied and computational mathematics, engineering physics, computer science, or similar programs where you have excelled.
  • Experience in optimization techniques is an advantage.


  • Fluent in Swedish and English
  • Programming skills including C++
  • Programming skills in Python and C# is an advantage 


Personal profile

In order to be successful you should be able to take your own initiatives and take responsibility for your work tasks. We would like to see that you are flexible and easily adapt to changes, and that you are meticulous in your work so that tasks are thoroughly completed. It is important that you have an analytical approach to problem-solving. As a person you should be optimistic and like to work both independently and in a group.

Working at RaySearch

RaySearch, a world leader in the field of advanced software for radiation therapy, offers a workplace with an open and positive atmosphere, where learning, creativity and collaborations are highly valued. Located in central Stockholm, RaySearch provides you with a unique opportunity to work in a fast growing, international company where you can be proud of the products and solutions that the company work towards. Read more about RaySearch.

Apply for this vacant position

You are welcome to send your application marked with “Master’s Thesis, Optimization 2” as soon as possible by clicking on the button below or by sending an email to work@raysearchlabs.com. Please include a resume, transcript of university records and any relevant scientific publications such as your bachelor thesis report and possible published papers. The selection and interviewing process will be ongoing.

For further questions please contact Kjell Eriksson, Chief Science Officer.