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PhD in Advanced Radiotherapy Treatment Planning

Research / Academic
Delft

Description:

Radiotherapy is a crucially important modality to treat cancer, with the majority of patients receiving radiation treatment at one point during the course of their disease. Intensity Modulated Proton Therapy (IMPT) is a novel, rapidly spreading type of radiotherapy, theoretically superior to traditional X-rays due to delivering doses more precisely, better protecting organs-at-risk. Unfortunately, this higher dose conformity increases sensitivity to errors caused by imperfect patient positioning, proton range calculations and organ motion uncertainties. To reach protons’ full tissue-sparing potential, the adequate, not over-conservative, and ultimately real-time handling of errors is crucially important.

The goal of this project is to develop novel radiotherapy algorithms that effectively incorporate errors in treatment planning, thus overcome the computational challenge of (ultimately real-time) error mitigation. Research will focus on Reduced Order Modelling (ROM) methods coupled to machine learning (ML) algorithms. ROM can effectively capture organ motion and thus represent the anatomy variations, whereas ML algorithms can link the anatomical changes to the corresponding changes in the dose distribution. Successful implementation of such algorithms will enable comprehensive robustness evaluation of proton and X-ray therapy plans, clinically applicable probabilistic optimization; and ultimately will pave the way towards near real-time dose calculation and online treatment adaptation. This will improve both IMPT and traditional X-ray therapy, reducing radiation side-effects and increasing the success rate of RT treatments.

The project will be carried out in close collaboration with the newly built Holland PTC (one of the 3 Dutch proton thearpy clinics) as well as Erasmus MC.

Requirements:

We at TU Delft are looking for an enthusiastic PhD student with a keen interest in developing numerical methods and software algorithms for advanced radiotherapy treatment planning. The candidate should meet the following requirements:

  • Solid background in applied mathematics and computational physics, especially in probability theory, numerical analysis, and model and algorithm development.
  • MSc degree in Applied Physics, Applied Mathematics, Medical Physics, Biomedical Engineering or equivalent.
  • Programming experience in at least one current language (e.g. Matlab, Python, C/C++).
  • Excellent communication skills in English, both in writing and speaking.
  • Good team-player, ability to work in a collaborative environment.
  • A background in radiotherapy or medical physics, as well as in reduced order modelling or machine learning approaches is a plus, but not necessary.

Salary Benefits:

TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.tudelft.nl/phd for more information.

For more information about this vacancy, you can contact Dr. Zoltan Perko, Assistant Professor, email: Z.Perko@tudelft.nl or tel.nr. +31 15 27 86821.

To apply for this PhD position, please send a detailed CV, a 1 page motivation letter and the contact information of 2 references via email to Anouk Nieuwesteeg at A.M.Nieuwesteeg@tudelft.nl. Applications will be evaluated on a first come, first served basis.
When applying for this position, please refer to vacancy number TNWRST18-070. 

 

Work Hours:

38 hours per week

Address:

Mekelweg 15