Complexity and biological evolution:
The quantitative study of complex systems, where interactions between simple components lead to complicated emergent behaviour, is a rapidly advancing field. Living organisms demonstrate immense complexity. How does this complexity arise from the process of biological evolution? We aim to show the key features of a biological environment that facilitate the evolution of complexity.

Reversible self-assembly of virus capsids:
Modelling the formation of protein coats that surround a virus' genetic information. These structures self-assemble from a number of identical subunits within the cell, and self-assemble reversibly, so that, for example, on changing the pH of the system the structure can be dissembled then reassembled. My work aims to provide a model for this process, complimenting recent energy landscape analysis and investigate the thermodynamics and mechanisms of the assembly, with possible applications in medicine and nanotechnology.

Deterministic assembly of polyomino structures:
Using 'building blocks' of patchy particles on a 2D lattice and a 'genome' of instructions on how these blocks interact allows large and complex structures to be grown from a small number of nucleus points. A well-defined complexity value can be assigned to structures assembled in this way. Genetic algorithms can be used to determine the correct genome for a particular structure, providing a flexible framework for modelling evolution with a non-trivial genotype-phenotype map. 2D self-assembly processes may also prove useful in creating structures like electric circuits on the nanoscale.