Open position: Research Associate in Mathematics
We are looking for a talented researcher to work with us on stochastic modelling of single cell dynamics. The position will be based at the South Kensington campus of Imperial College London at the heart of London’s cultural centre. The position is for two years and funded by UKRI through a Future Leaders Fellowship.
The project will develop theory and inference methods for data-driven models of cell populations. A goal is to understand how cellular heterogeneity and history limit cellular behaviour in heterogeneous dynamic environments. The project will involve stochastic modelling of cell growth, division, and gene expression to quantify decision making in bacteria and mammalian cells. Useful skills include (i) knowledge of stochastic processes and master equation modelling, (ii) statistical inference from time-series data, and (iii) computational single-cell biology. The successful candidate will have the opportunity to collaborate with leading experimental groups.
More details here: https://www.imperial.ac.uk/jobs/description/NAT01219/research-associate-mathematics
See also: jobs.ac.uk
Some useful references
F. A. Hughes, A. Barr, P. Thomas “Patterns of interdivision time correlations reveal hidden cell cycle factors” biorxiv
B.M.C. Martins, A.K. Tooke, P. Thomas, J.C.W. Locke (2018) “Cell size control driven by the circadian clock and environment in cyanobacteria” PNAS 115, E11415-E11424
M. Voliotis, P. Thomas, R. Grima, C.G. Bowsher (2016) “Stochastic simulation of biomolecular networks in dynamic environments” PLoS Comput Biol 12, e1004923