PhD Research Studentships

Multi-physics computational model of cancer dormancy in bone

Supervisor: Claire VILLETTE
Apply by:17 February 2026
Start in:September (Semester 1)

Description

Context:

Breast cancer metastases to bone are associated with a poor prognosis and are often incurable. Systemic spread of cancer cells from the primary site is now understood to be an early event, followed by a potentially prolonged state of dormancy, wherein cancer cells are non- or slow-growing and chemo-resistant.

Bone tissue undergoes a continuous remodelling process to maintain functional and mechanical integrity, whereby osteoclasts degrade bone matrix and osteoblasts form new tissue. Their activity is modulated by mechanical loading of the tissue, allowing skeletal adaptation to sustained changes in physical activity regimens. The bone microenvironment has a decisive influence on cancer cell proliferative state. In particular, it is considered that osteoblasts may promote dormancy while osteoclast-mediated bone resorption correlates with dormancy exit. A wide body of evidence also supports the role of innate and adaptive immune cells in regulating metastasis development.  Due to the load-bearing nature of bone tissue, mechanical loading also constitutes an important environmental variable in the context of metastasis. It is generally associated with reduced proliferation of bone metastasis in vitro and in vivo, although it may also activate osteoclasts which in turn may reactivate dormant cancer cells.

Project aim and objectives:

This project aims to develop a computational model of cancer dormancy in bone, able to capture the respective effects of the bone microenvironment agents on cancer dormancy or proliferation. Its final goal is to support the design of therapeutic interventions against bone metastases. The main activities foreseen for this project include:

  1. Taking our preliminary agent-based model of metastatic bone remodelling to the next level by introducing immuno-modulation and its interactions with mechanical loading. This model will combine numerical representations of cell population dynamics, cellular cross-talk and mechanical load transfer.
  2. Using in-vitro experiments to inform model calibration.
  3. Screening through configurations of the bone microenvironment to uncover scenarios with potential therapeutic benefit.

The exact scope of the project is open to refinements based on the successful candidate’s suggestions.

Candidate profile:

We are looking for candidates who hold a degree in Bioengineering, Biomedical Engineering, Mechanical Engineering, Computing, Applied Maths, or related disciplines. Previous experience in computational modelling or evidence of coding literacy is required.  The successful candidate will be expected to conduct some in-vitro experiments to calibrate the models. Previous experience in cell culture is an advantage but not essential, as strong support is available in-house to acquire the related skills.

Funding

Funded by: EPSRC
Home students only are eligible for funding/

Eligibility

  • The minimum requirement for this studentship opportunity is a good honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of minimum score of 6.0 in each of Writing, Listening, Reading and Speaking).
  • Candidates are expected to start in September (Semester 1).

Contact

For informal enquiries about this opportunity, please contact Claire VILLETTE.

Apply

Start an application for this studentship and for entry onto the PhD FT Medical Engineering full-time programme (Semester 1 / September start):

Apply Now »

Please be sure to quote the reference "SEMS-PHD-707" to associate your application with this studentship opportunity.

Related website:https://www.thebmecalab.com/
SEMS Research Centre:
Bioengineering
Keywords:Cancer Biology, Cell Biology, Immunology, Bioengineering, Biomedical Engineering, Mechanics, Mathematical Modelling, Biomechanics, Tissue Engineering, Computational Physics