The properties of many biological systems emerge through the interactions
of their constituent components; the development from a single cell to a fully formed organism
is the results of orchestrated interactions between millions of cells, and also disease states
such as cancer emerge through physical and biochemical interactions between millions of cells
that are migrating, proliferating and dying.
In order to understand how complex biological phenomena arise from simpler systems we need mathematical techniques that can connect microscopic interactions with macroscopic dynamics. Linking the underlying microscopic stochastic dynamics with macroscopic and largely deterministic phenomena is achieved through homogenisation techniques, that connect finitely many stochastic processes to a continuum density of states often characterised by partial differential equations.
We are seeking a motivated PhD-student that will develop and analyse microscopic
cell-based models of tumour growth. Typically such models are on the single-cell scale and capture
processes such as cell migration, proliferation and differentiation. Possible topics are micro-mechanical
models of cell-migration, analysing kinetic equations of collective cell migration and developing new
techniques for correlation closure in kinetic equations. Programming will typically play a role in all these projects.
The successful candidate should have finished a masters degree in mathematics or mathematical statistics with excellent results. A background in partial differential equations, stochastic processes and programming is advantageous.
The applicant will be located at the Mathematical Sciences a joint department within Gothenburg University and Chalmers University of Technology. The research will be conducted within a larger project that focuses on the modelling of complex biological phenomena using mathematical and statistical tools. The student will be supervised by assistant professor Philip Gerlee.