This project offers a computational research project utilising Monte Carlo radiation transport codes and a commercial clinical radiotherapy treatment planning system. Vendor beam models are typically derived
from relative dosimetric measurements supplied by clinical users. Because these relative dosimetric measurements are from ion chambers and diodes they do not necessarily satisfy Bragg-Gray cavity conditions in the penumbra and umbra. The resulting vendor beam models embed detector-response artefacts rather than true physical dose.
The major computational aspect of the project is to reverse-engineer the beam model employed by the Elekta Monaco treatment planning system. The student will use BEAMnrc to construct a matched Monte Carlo source model that reproduces the relative signals used for commissioning, quantify absolute dose discrepancies in the beam periphery, and examine spectral differences between the Monaco-effective model and a physically realistic beam model. This provides independent dose calculation capability for Monaco and insight into the limitations of relative-dosimetry-based modelling.
Suitable for a student interested in medical physics, computational physics, or radiation dosimetry. Python or Monte Carlo experience is helpful but not required; training will be provided. The project is designed to be completed within the 10-week timeframe while contributing to longer-term research on accurate and accessible radiotherapy.
Supervisors
Primary Supervisor: Bryn Currie
Other Supervisor(s): Steven Marsh
Application and funding
This is a UC Commitments Summer Scholarship research project. Emailed applications will not be considered. Find out more here: University of Canterbury Scholarship Portal - UC Commitments Summer Scholarship
Final date for receiving applications
25 September 2026
