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The Optimization of Medical Accelerators (OMA) project, coordinated by Prof Carsten Welsch, member of the Cockcroft Institute and Head of the Liverpool Physics Department, held an international school on Monte Carlo simulations at Ludwig Maximilian University of Munich, Germany, between 6 – 10 November 2017.
The School programme was delivered by international experts from institutions including CERN, LMU Munich and University of Barcelona. Dr Alfredo Ferrari from CERN coordinated the overall programme. The event covered the fundamentals of Monte Carlo simulations and combined lectures with hands-on workshops that gave participants the opportunity to study the different techniques in dedicated computer classes. The Monte Carlo codes FLUKA, PENELOPE and GEANT4 were all covered during the week, providing a comprehensive overview of some of the most utilized expert codes in accelerator science.
The event brought together Fellows from two major training initiatives: OMA and LIV.DAT, providing opportunities for discussing specific research project needs and networking. The Monte Carlo approach is very important for medical accelerators in particular as it allows understanding both, beam delivey to the patient, as well as treatment planning in unparalleled detail and completeness. This technique is also very relevant for other research areas and is one of the three scientific work packages in the LIV.DAT Center for Doctoral Training.
This School was part of an international training programme delivered within the OMA project. OMA joins universities, research centres and hadron therapy facilities with industry partners to address the challenges in treatment facility design and optimization, numerical simulations for the development of advanced treatment schemes, and in beam imaging and treatment monitoring. The network consists of an international consortium of more than 35 partner organizations and provides a wide ranging training programme comprising schools and workshops.
More details can be found on the School website.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 675265.