A 2026 Crick PhD project with Zena Hadjivasiliou.

Project background and description

A hallmark of embryo development is the generation of spatial patterns guided by morphogen gradients and gene regulatory networks (GRNs). This has led to an extensive body of work that explores the interaction between long-range signalling molecules and cellular response. However, we understand little about the physical mechanisms via which cellular and tissue dynamics contribute to spatial patterning, and emergent properties due to feedback between cell behaviour, such as proliferation and 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.

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