Available
Project number:
2025_103
Start date:
October 2025
Project themes:
Main supervisor:
Consultant Haematologist and Honorary Senior Lecturer/Adjunct Senior Lecturer
Co-supervisor:
Professor Richard Dobson
Additional Information:
Modelling patterns of relapse in Multiple Myeloma
Multiple Myeloma is an incurable malignancy with multiple relapses. There are several risk factors that can prognostically determine patients who may progress early after induction treatment. However, there is little research in determining patterns of Multiple Myeloma natural history after induction (first) therapy. This may lead to overtreatment of patients who have non-progressive disease at relapse. On the other hand, another group of patients may relapse aggressively and become refractory to different lines of therapy. In this cohort, a different treatment regimen incorporating novel treatment modalities may lead to longer remissions.
This project aims to define different patterns of disease relapse based on clinical laboratory data. The second objective is to create a prognostic model for patients at relapse. The student will learn to use Cogstack to collect clinical laboratory and other relevant data for each patient over the treatment time horizon. They will then create a model to categorise patients at relapse. Finally, they will identify factors that can accurately classify patients at relapse to the different groups identified earlier. Most of the data analysis and modelling will be done using Python.
As patients with symptomatic Multiple Myeloma will likely be on treatment at multiple times of their lives, this project will hopefully increase the efficiency of resource allocations in treating these patients. Furthermore, individualised treatment strategy at relapse will hopefully lead to better overall outcome for all patients with Multiple Myeloma.
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