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The dissertation is a 10,000 written thesis based on an extended research project which lasts throughout Trinity Term (your third term of study) and the Long Vacation. This is a substantial piece of work and accounts for 40% of the total marks awarded for the MSc degree. 

The purpose of the dissertation and is to ensure that you have a good understanding of research practice and study design. The dissertation content is designed to assess you on your academic ability, critical thinking, originality and your understanding of the pragmatics of research.  Dissertations on this course are usually based on applied laboratory or computational work.

For this project you will be embedded in one of the research laboratories within the University's Medical Sciences Division,  most usually within the Department of Oncology, or with researchers based in the Oxford University Hospitals Department of Medical Physics and Clinical Engineering . A list of dissertation projects and potential supervisors will be provided in Michaelmas Term. You will need to discuss with potential supervisors and decide on a project by the January. There is no requirement to identify a project or supervisor before you apply to this course. 

After submission of the thesis, you will also be required to present a scientific poster based on your work at the Master's Dissertation Showcase in September. This is a compulsory part of the course and counts towards your dissertation grade. 

Dissertation timeline: 

October to December Project application process begins
January Projects allocated
April to August Undertake research and write up findings
August Submit dissertation
September Master's Dissertation Showcase

Example projects:

These are example project titles to give an idea of the sort of projects that are available with the Department of Oncology, OUH, or other collaborating groups within the University or beyond. There are no guarantees these or similar projects will be available in future academic years.

  • An investigation into the role of iron in radiosensitisation and the FLASH effect on tumour versus normal tissue - Lab-based
  • Implementation and Clinical Application of T1 Mapping in the Lung MRI - Clinical
  • Optimisation of Synthetic T1-Weighted Imaging of the Brain - Computing-oriented
  • A Machine Learning PyTorch-Based Approach for Diagnosis and Staging of Multiple Sclerosis using Metabolic (C-13), Diffusion, and Perfusion MRI images of the Brain - Computing-oriented
  • Analysis of Organ Doses received from Interventional Fluoroscopy Scans and Potential Risks of Cardiovascular and Cerebrovascular disease - Literature review
Publications from Previous Dissertation Projects:

NB: Publication from a Dissertation Project is not guaranteed, and is not required for achieving the highest marks in the assessment of the Dissertation.

  • Cook, E.L., Su, KH., Higgins, G.S. et al. Data-driven gating (DDG)-based motion match for improved CTAC registration. EJNMMI Phys 11, 42 (2024).
  • Dedja, M., Mehranian, A., Bradley, K.M. et al. Sequential deep learning image enhancement models improve diagnostic confidence, lesion detectability, and image reconstruction time in PET. EJNMMI Phys 11, 28 (2024).
  • Bourigault, P., Skwarski, M., Macpherson, R.E. et al. Timing of hypoxia PET/CT imaging after 18F-fluoromisonidazole injection in non-small cell lung cancer patients. Sci Rep 12, 21746 (2022).
  • Bourigault, P., Skwarski, M., Macpherson, R.E. et al. Investigation of atovaquone-induced spatial changes in tumour hypoxia assessed by hypoxia PET/CT in non-small cell lung cancer patients. EJNMMI Res 11, 130 (2021).