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Modelling hypo-fractionated radiation therapy

  • Full or part time
  • Application Deadline
    Wednesday, January 23, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

About This PhD Project

Project Description

Adaptive Radiotherapy: Engineering the radiobiological tumour for improved radiation success (5 PhD Scholarships)

To celebrate the University's research successes, the University of Hull is offering a full-time UK/EU/International PhD Scholarship for candidates applying for each of the following projects as part of a new research cluster.

Studentships will start on 16th September 2019

Summary of Cluster

Radiotherapy is a key cancer treatment strategy, but remains an underrepresented area of research focus in the UK and worldwide. The Adaptive Radiotherapy PhD studentship cluster is focused on radiotherapy research training and capacity building at the University of Hull and in the Hull and East Yorkshire NHS Trust (HEYH-NHS). In this truly multidisciplinary cluster, students will have the opportunity to work with experts from a wide variety of areas, including cancer biology, cancer therapy, and radiobiology (Pires), radiosensitiser synthesis and validation (Boyle), development and validation of novel imaging tracers (Archibald), computational modelling in biomedical sciences (Turner), radiation treatment plan modelling and radiology (Beavis and Moore), clinical oncology (Lind and Roy). The students will be embedded in an active, dynamic, research environment, with access to all research facilities both at the University of Hull relevant to the cluster (Biomedical Sciences, Chemistry, Computer Science), as well as the Medical Physics facilities, Molecular Imaging Research Centre and instruments at Castle Hill Hospital.

PhD Project

Modelling hypo-fractionated radiation therapy, with Professor Andy Beavis (), Dr Craig Moore, and Dr Alex Turner

Hypo-fractionated radiotherapy is a strategy in which the total dose of radiation is divided into large doses and treatments are given over a short period of time when compared with traditional radiotherapy regimens. This strategy has advantages in terms of reducing the cost of therapy associated with cancer radiotherapy, but further work remains to be done regarding the safety and efficacy associated with this strategy. Importantly, the use of radiobiology biomarkers could allow for a clinically relevant assessment of efficacy of hypofractionation. In this project we will be using in silico modelling and simulations to investigate the impact of the use of ‘hypoxia scores’ or a ‘hypoxia map’ in increasing the effectiveness of fractionated radiotherapy strategies. The models developed will also assess whether targeted therapy of relevant signalling pathways could constitute novel biomarkers for clinically relevant hypo-fractionation sensitising strategies. The successful candidate will be expected to have a solid knowledge base in physics or computer science, and, ideally, some knowledge on cancer biology and medical physics. The candidate must also show a willingness to work in a multi-disciplinary environment with NHS researchers, and embrace the area of model development for radiotherapy planning.

Applicants should have a 1st class undergraduate degree in Physics, Computer Science, Medical Imaging, or a related discipline, or a Masters level research qualification in a relevant discipline. A 2:1 may be considered, if combined with relevant experience.

To apply for these Scholarships please click on the link below.

https://www.hull.ac.uk/choose-hull/study-at-hull/admissions/postgraduate/how-to-apply.aspx

Full-time UK/EU and International PhD Scholarships will include tuition fees and maintenance (£14,777 in 2018/19) for three years, depending on satisfactory progress.

PhD students at the University of Hull follow modules for research and transferable skills development and gain a Masters level Certificate, or Diploma, in Research Training, in addition to their research degree.

Interviews will be held between 7th and 27th February 2019

Successful applicants will be informed of the award as soon as possible and by 15th March 2019 at the latest.

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