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Machine Learning for Discovery of Patient Journey-Wide Phenotypes and Colorectal Cancer Stratification

  • Full or part time
  • Application Deadline
    Monday, February 25, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Supervisors: Dr. Ian Overton (QUB), Dr. Paul Miller (QUB), Dr. Helen Coleman (QUB), Dr. Seanna McTaggart (LifeArc)

Colorectal cancer is the second highest cause of cancer mortality, associated with >880,000 deaths per annum worldwide. This project seeks to develop novel approaches for stratification of colorectal cancer patients in order to help inform clinical decision-making. For example, while a proportion of stage II colorectal cancer patients benefit from chemotherapy, it can be challenging to identify which specific patients will benefit [Kannarkatt et al. Journal of Oncology Practice 2017].

Cutting-edge informatics techniques will be applied to large datasets, including substantial linked clinical and demographic data, in order to discover fingerprints of individual characteristics that define new phenotypes across the patient journey. These data-driven patient phenotypes may include factors, for example relating to lifestyle, that influence the molecular processes driving cancer progression. Therefore discovery of patient phenotypes may define new cohorts for development of novel phenotype-specific molecular stratification approaches.

Work during this four year studentship will be primarily based in the Overton group at Queen’s University Belfast (https://go.qub.ac.uk/IanOverton) and associated with the Health Data Research UK Wales and Northern Ireland substantive site (https://www.hdruk.ac.uk). The studentship includes six months to be spent at the LifeArc Centre for Diagnostics Development in Edinburgh, an ISO13485 certified environment (https://www.lifearc.org). The successful candidate will benefit from LifeArc’s considerable diagnostics development expertise, helping to ensure the anticipated novel diagnostic software is competent for potential clinical use.

Eligibility

For more details about eligibility, please see:

https://www.epsrc.ac.uk/skills/students/help/eligibility/

For further information, please contact Ian Overton in the first instance:

Funding Notes

This EPSRC CASE studentship has a significantly enhanced stipend (starting at £21,009 per annum) and also covers tuition fees at the rate for European/UK students. All funding is subject to final sign-off of the collaboration agreement between LifeArc and Queen’s University Belfast. Any international (non-EU) applicants would have to pay the shortfall of fees at the international rate and would be considered for eligibility on a case by case basis.

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