movement, and cellular signalling. The focus of this project is to develop theoretical frameworks, grounded in and coupled to experimental observations, to advance our understanding of how tissue organization and cell dynamics interact with biochemical patterning.
The student will build on theoretical tools developed in the Hadjivasiliou lab to make predictions about how tissue growth, cell movement and proliferation impact the interpretation of extracellular signals, and how feedback between intracellular signalling and cell dynamics drives emergent properties at the tissue-level such as robustness and scaling. The project will involve collaborations with experimental colleagues, offering opportunities to work directly with experimental data.
The host lab will provide training in techniques necessary for the project such as best coding practices, High Performance Computing, analytical and numerical techniques to solve ODEs/PDEs and investigate dynamical systems, and Machine Learning for data analysis. More broadly, the student will develop the skills to independently apply physics and mathematics to biological questions and work collaborative at the interface of these disciplines.
Candidate background
This project will suit candidates with a background in mathematics, physics, computer science, engineering or related discipline and an interest in biology. The ideal candidate will have a strong interest in bridging the fields of physics, computational and mathematical biology, developmental and evolutionary biology, and a willingness to work with experimental data and interact with biologists. Some experience in computational coding is strongly encouraged.
Lab-specific question
Looking at the research undertaken in our lab, what aspect would you be most interested in exploring further? Drawing on your own research experience, what perspective, skill or approach would you bring to investigating it?
Funding Notes
Successful applicants will be awarded a non-taxable annual stipend of £27,715 plus payment of university tuition fees. Students of all nationalities are eligible to apply.
References
- Autorino, C., Khoromskaia, D., Harari, L., Floris, E., Booth, H., Pallares-Cartes, C., . . . Petridou, N. (2025) Preprint: A closed feedback between tissue phase transitions and morphogen gradients drives patterning dynamics. Available at: bioRxiv https://www.biorxiv.org/content/10.1101/2025.06.06.658228v1.full.pdf
- Stapornwongkul, K.S. and Vincent, J.P. (2021) Generation of extracellular morphogen gradients: the case for diffusion. Nature Reviews Genetics 22: 393–411. PubMed abstract
- Serrano Nájera, G., Plum, A.M., Steventon, B., Weijer, C.J. and Serra, M. (2025) Control of tissue flows and embryo geometry in avian gastrulation. Nature Communications 16: 5174. PubMed abstract
- Spiess, K., Taylor, S.E., Fulton, T., Toh, K., Saunders, D., Hwang, S., . . . Verd, B. (2024) Approximated gene expression trajectories for gene regulatory network inference on cell tracks. iScience 27: 110840. PubMed abstract
- Romanova-Michaelides, M., Hadjivasiliou, Z., Aguilar-Hidalgo, D., Basagiannis, D., Seum, C., Dubois, M., . . . Gonzalez-Gaitan, M. (2022) Morphogen gradient scaling by recycling of intracellular Dpp. Nature 602: 287–293. PubMed abstract
