PhD Studentship in “Multi-scale mathematical models to predict prostate cancer progression and treatment response” (2024)

PhD studentship in the Groups of “Mathematics Applied to Biology” and “Numerical Analysis and Scientific Computing” at the University of Sussex (UK), with the collaboration of the “Group of Numerical Methods in Engineering” at the University of A Coruña (Spain).

What you get

  • Fully-paid tuition fees for three and a half years at the home fee status.
  • A tax-free bursary for living costs for three and a half years (£18,622 per annum in 2023/24).
  • Additional financial support is provided to cover short-term and long-term
  • If you are not a UK national, nor an EU national with UK settled/pre-settled
    status, you will need to apply for a student study visa before admission.

Type of award

PhD Studentship

PhD project

Prostate cancer (PCa) ranks as the second most prevalent cancer among men worldwide, also constituting the fifth cause of cancer-related death. While advances in screening and diagnosis enable early detection, therapies for late-stage disseminated disease remain primarily palliative. Recent interdisciplinary studies highlight the urgency for evaluating new therapeutic strategies to manage advanced PCa dynamics and the emergence of drug resistance. Recently, Ferroptosis, a form of cell death triggered by lipid peroxidation induced by agents such as RSL3, has emerged as a focus of attention. Our project will use data from both in vitro and in vivo human and murine PCa models, including the multistage transgenic TRAMP model, to investigate ferroptosis induction by RSL3 and its augmentation through iron supplementation. Single and multi-drug treatment strategies for PCa, incorporating pro-ferroptotic approaches either alone or in combination with enzalutamide, will be one of the focuses of this project.

Mathematical oncology plays an increasingly pivotal role in cancer research, aiding experimental studies to unravel cancer dynamics and devise personalised therapeutic strategies against this formidable disease. This project aims to construct and validate data-driven continuum and hybrid mathematical models of vascular tumour growth, shedding light on the interaction between novel therapies and PCa cells, with the support of prior experimental evidence and mechanistic insights. The project will involve developing and analysing PDE models, ABM models, and their integration to map cellular behaviour to macroscopic mechanisms and predict therapeutic outcomes. The models developed within the PhD will elucidate how drug-cell and cell-cell interactions shape tumour growth dynamics and the efficacy of diverse therapeutic approaches. Specifically, we will focus on mathematically representing the varied mechanisms contributing to drug resistance, cellular metabolic alterations during treatments, and their repercussions on cancer behaviour, including the development of metastases.

The project endeavours to bridge mathematical rigour with clinical utility, advancing our understanding of PCa dynamics and guiding the development of effective therapeutic strategies.  A crucial aspect of this project will involve the analytical and numerical study of dynamical systems, alongside statistical comparisons between simulations and experimental data.  Collaboration is key to research, and the successful candidate will collaborate closely with clinicians, biologists, and oncologists from diverse backgrounds to ensure the relevance and applicability of their models across various patient populations.

Our PhD program welcomes students of all genders, ethnicities, races, sexual orientations, abilities, and socio-economic backgrounds. We believe diversity drives innovation in research.

In this project, the successful candidate will develop expertise in mathematical modelling, computational biology, mathematical oncology, statistics, and numerical methods. They'll learn to analyse and interpret PCa data in a collaborative and supportive environment. 


The work on this project will involve:

  • Development and qualitative analysis of PDE models for cancer dynamics and drug-cancer cell interactions.
  • Analysis of experimental data.
  • External collaboration with interdisciplinary teams (Experimental oncologists).
  • Elaboration of scientific articles and conference presentations.


Applicants must hold, or expect to hold, at least a UK upper second class degree (or non-UK equivalent qualification) in Physics/Mathematics, or a closely-related area, or else a lower second class degree followed by a relevant Master's degree.

This award is open to UK and International students.


14 June 2024 23:45

How to apply

Apply through the University of Sussex on-line system.

Select the PhD in Physics/Mathematics, with an entry date of September 2024.

In the Finance & Fees section, state that you wish to be considered for studentship MPS/2024/CER

We advise early application as the position will be filled as soon as a suitable applicant can be found.

Due to the high volume of applications received, you may only hear from us if your application is successful.


Contact us

If you have practical questions about the progress of your on-line application or your eligibility, contact

For academic questions about the project, contact Dr Cerasuolo at  or Dr Van Yperen at


At level(s):
PG (research)

Application deadline:
14 June 2024 23:45 (GMT)


The award is available to people from these specific countries: