About the Project
Student Background: Mathematics/Statistics, Theoretical Physics, Engineering (Biological knowledge not required)
Description: Cells decide when to divide based on the dynamics of intracellular reaction networks. This behaviour often varies drastically from cell to cell because their biochemical reactions are stochastic. Our group develops theoretical methods using a mix of stochastic processes and nonequilibrium physics to understand the cell division dynamics of bacterial and mammalian cells. We are particularly interested in developing theory for agent-based models, a novel approach that allows tracking every individual in a growing and dividing cell population at the experimental single-cell resolution. Such approaches are now becoming increasingly important in cell biology, medicine and biotechnology.
The aim of this project is to understand how stochasticity in gene regulatory networks affects cellular behaviour. To this end, you will extend the common Chemical Master Equation approach to include cell growth and division. You will develop cutting-edge analytical methods to approximate agent-based models. Using these methods, we will investigate cell-to-cell heterogeneity in lineage trees, which can be measured in experiments. Possible applications to experimental data will explore how cells respond to stress or drug treatment. The project provides first-hand, state-of-the-art training in stochastic processes, biomathematics and computational biology.
This is a well funded 3.5-year position for UK or EU nationals. We are seeking applications from highly motivated theorists with excellent intuition, strong analytical skills and a background in a quantitative discipline (mathematics, physics, engineering, computational biology). Expertise in stochastic processes, Markov chains and/or analysis of the Chemical Master Equation will be beneficial. As a member of the Biomathematics group you will benefit from the thriving environment at the Department of Mathematics, the EPSRC Centre for Precision Healthcare and a range of world-leading experimental collaborators (Dr J Locke, University of Cambridge; Dr A Barr, MRC London Institute of Medical Sciences). For more information about the group, please visit www.imperial.ac.uk/people/p.thomas. For information about the PhD programme, please visit http://www.imperial.ac.uk/mathematics/postgraduate/research-phd-in-mathematics/
Applications should be sent informally to [Email Address Removed] including a brief motivation, CV and a transcript of records.
We are also interested to hear from exceptional international students regarding several competitively funded opportunities.
Sources, propagation and consequences of stochasticity in cellular growth. P Thomas, G Terradot, V Danos, AY Weiße. Nature Communications 9, 4528. https://doi.org/10.1038/s41467-018-06912-9
Analysis of cell size homeostasis at the single-cell and population level. Thomas P (2018) Frontiers in Physics 6:64.
Intrinsic and extrinsic noise of gene expression in lineage trees. Thomas P (2019) Scientific Reports 9, 474. https://doi.org/10.1038/s41598-018-35927-x
Based on your current searches we recommend the following search filters.
Based on your current search criteria we thought you might be interested in these.