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AI fault diagnosis and intelligent control of medical linacs for Africa and FELs

Cockcroft Institute

About the Project

A studentship is available from October 2021 on the use of artificial intelligence and machine learning to investigate fault diagnosis and intelligent control of medical linacs for use in lower-middle income countries.

Worldwide in 2018 alone, 9.6 million people died and 43.8 million people were living with cancer. Current projections anticipate an increase to approximately 13 million related deaths by 2030, with 60-70% of cases in Low and Middle-Income countries (LMIC). While cancer care is a global challenge, some areas are far more affected than others due to a lack of access to suitable technology, lack of trained staff, higher technology failure rates and lack of spare parts leading to lower patient throughput. In Low- and Middle-Income countries (LMICs), patient outcomes are significantly worse than in High Income Countries. The Global Task Force on Radiotherapy for Cancer Control (GTFRCC) estimated that 12,600 megavolt-class treatment machines will be needed to meet demand in LMICs by 2035 (there are currently only 385 machines). Currently the staff training burden and the high downtime (close to 50% on average in Africa) is a key reason for the limited number of radiotherapy provision in LMIC. Key to overcoming this global challenge are technologies which automate processes, reduce burden on staff time, decrease downtime, improve patient throughput and have an impact on operational capacity. This project will focus on the following three challenges

• Prediction of faults before they happen using Artificial Intelligence (AI)

• Diagnosis of faults using AI

• Intelligent control of medical linacs

The project will also investigate failure in similar components found in Free Electron Lasers, using CLARA as a test bed.

The applicant will be expected to have a first or upper second class degree in electronic engineering, physics, computer science or other appropriate qualification. Experience in accelerator and/or AI is desirable but not essential. A full graduate programme of training and development is provided by the Cockcroft Institute. The student will be based primarily at the Cockcroft Institute at Daresbury. You can find out more about being a PhD student at the Cockcroft Institute here, where you can download an application form and also find out about the other PhD projects available at the Cockcroft.

To apply for this project, fill in the application form and email it with your CV to .

Potential applicants are encouraged to contact Prof Graeme Burt () for more information. This position will remain open until filled.

Anticipated Start Date: October 2021 for 3.5 Years

Funding Notes

Upon acceptance of a student, this project will be funded by the Science and Technology Facilities Council for 3.5 years; UK and other EU citizens are eligible to apply. A full package of training and support will be provided by the Cockcroft Institute, and the student will take part in a vibrant accelerator research and education community of over 150 people. An IELTS score of at least 6.5 is required.


Expanding access to radiotherapy in sub-Saharan Africa, Lancet Oncol. 2020 Aug; 21(8): 1019.

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