Available
Project number:
2025_91
Start date:
October 2025
Project themes:
Main supervisor:
Reader in Bioinformatics
Co-supervisor:
Additional Information:
AI/ML Approaches for Integrative Bioinformatics of Thoracic Cancer
Earlier diagnosis, better prognostication and individualised treatment planning represent acute challenges for cancer where there remains a clinical need to improve patient-related outcomes. This is particularly true for thoracic-based cancers such as lung, mesothelioma and oesophageal cancer that are associated with a poor prognosis despite multimodality ‘curative’ treatment (≤10% 10-year survival rate). Improved clinical decision support stands to benefit from methods that can integrate data of multiple modalities that reflect longitudinal outcomes. Analyses of such large and heterogeneous data necessitate advanced AI/ML methodologies to ensure accurate prognostic prediction and realise the potential of personalised treatment.
We have developed methodologies based on deep learning and mathematical optimisation for data integration and feature engineering that can address current challenges in multi-modal data integration and predictive analysis. These methodologies will be extended and enhanced, through the application on thoracic malignancy data that we have collected. The workplan envisioned in the project will comprise an integrated pipeline for data representation and analysis that will span various AI/ML methods and data types (imaging, clinical and omic data). The outcome will be an informatics pipeline of multiple levels, each level addressing an independent computational task but also collectively complementing each other in terms of supporting clinical decision, enhancing accurate diagnosis, prognosis and treatment prediction in thoracic-based cancers.
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 6 February 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in April 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at