Research Fellow: Quality Assurance (QA) and Validation of Deformable Image Registration (DIR) in Radiotherapy
Position: Research Fellow
Institution: University College London
Application closes at: Jan 20th, 2020 18:40
We invite applications from highly motivated individuals for this postdoctoral research position which will focus on the area of quality assurance (QA) of deformable image registration in radiotherapy. This project will provide an exciting opportunity to work in a collaboration between The Centre for Medical Image Computing (CMIC) at University College London and The National Physical Laboratory (NPL). This project is funded through the Department for Business, Energy & Industrial Strategy (BEIS) Industrial Strategy Challenge Fund in Medical Imaging.
Deformable Image Registration (DIR) has been proposed for a wide range of applications in radiotherapy, including treatment planning, guiding and adapting delivery to account for changes to the patient’s anatomy, and follow-up studies investigating the effects and outcomes of radiotherapy treatments. Various commercial radiotherapy vendors now offer DIR algorithms within their software. However, a current challenge for radiotherapy departments is in the safe implementation of, and confidence in using DIR algorithms. Challenges include: how to robustly quality assure (QA) and validate DIR, what to do if there is a problem with the registration with DIR in a clinical system and the need for clinically relevant metrics. Various recommendations have been described in the literature, however a recent survey amongst UK centres has shown that there is a need for further research and guidance to address the above challenges. These areas will be the focus of this project.
It is expected that the outcomes of this project will lead to presentations at international conferences and in high impact journals and will ultimately result in national guidelines and best practice for the safe use of DIR for clinical applications in radiotherapy. This demanding but exciting project has the potential for direct and lasting clinical impact and will give the candidate the opportunity to closely collaborate with clinical teams (oncologists, medical physicists, radiographers) as well as academic researchers from UCL and NPL.
The position is being offered on a UCL Grade 7 - full time for 6 months or part time 50% FTE for 12 months, with the possibility of extending the position for a further 6 months (12 months part-time). The anticipated start date will be January 2020 or as soon as possible after this date.
Candidates must possess an undergraduate degree, or equivalent in Computer Science, Engineering, Physics, Mathematics or related subject. A PhD (or about to submit a PhD) in Computer Science, Engineering, Physics, Mathematics or equivalent experience is essential. Experience of image processing and/or computer vision, ideally for medical images, is essential. Experience of Python and/or C++ and/or MATLAB programming and software development is essential. In addition, experience of working in a multi-disciplinary team including clinicians, medical physicists, and computer scientists is desirable.
Appointment at Grade 7 is dependent upon having been awarded a PhD. Or if about to submit a PhD, the appointment will be at Grade 6B (£31,479 - £33,194 salary, inclusive of London Allowance) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.
For informal queries about the position, please contact Dr Jamie McClelland (email@example.com) and Dr Mohammad Hussein (firstname.lastname@example.org).