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CS - Dr Weini Huang

Stochastic modelling of immune-cancer interactions under immunotherapies 

Supervisor: Dr Weini Huang

Project description:

Cancers are resilient biological systems and often come back after primary treatments. There is evidence that immune cells can suppress the emergence of cancers in early stages. For example, the incidence rates of childhood lymphoid leukaemia were found to be 20% lower in populations, where children were exposed to early immune challenges. Immune recognition and immune escape of tumour cells can be important and lead to different resilient outcomes in cancer progression among individuals.    

We have previously built a stochastic model of immune-cancer interactions, where antigenic mutations arise in cancer cells in divisions and can cause the reactions of corresponding immune cells. This project will focus on modeling the immune-cancer interactions in the context of immunotherapies. Here we will explore the detailed microscopic mechanisms of the recruitment of immune cells as well as the impact of immunotherapies on immune-cancer interactions. We will explore the application of our theoretical model by searching genetic footprints including those on chromosomal and extra-chromosomal DNA, which maybe differ under different outcomes of immunotherapies.  

Analytical work will involve using, for example, probabilistic and Markov models to calculate the distributions of these genetic footprints in cell populations. We will use computational simulations and Bayesian statistics to compare the mechanistic models with measured genetic patterns. These will be done in cooperation with our partner research groups in cancer biology. The candidate should hold a BSc, MSc or an equivalent degree in applied mathematics, physics, computer science or computational biology.

References:

Long, Morison et al. (2025) Cancer-immune coevolution dictated by antigenic mutation accumulation. eLife. 

Morison et al. (2025) Single-cell mutational burden distributions in birth-death processes. PLoS Comput. Biol. 

J. Lange et al. (2022). The evolutionary dynamics of extrachromosomal DNA in human cancers. Nature Genetics. 

Funding Notes:

This project is open to candidates applying for CSC/EPSRC/Underrepresented Studentships and self-funded candidates.

Further information: 
How to apply 
Entry requirements 
Fees and funding

PhD Information Session 2026:
On Wednesday 14 January, we will be holding a short information session about PhD studies in Mathematics at QMUL. For full details about the event, please visit: https://www.qmul.ac.uk/maths/postgraduate/postgraduate-research/phd-information-session-2026/

 

As one of the UK’s most diverse universities, QMUL fosters an inclusive and supportive academic community.

The School of Mathematical Sciences is committed to the equality of opportunities and to advancing women’s careers. As holders of a Bronze Athena SWAN award, we offer family-friendly benefits and support part-time study.  

 

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