The emergence of antibiotics resistance in bacteria and new organisms such as SARS-CoV-2 has major ramifications for public health. An important steppingstone in the development of strategies to combat them is to understand how they have evolved. The development of powerful algorithms and mathematical theory to describe and understand the evolution of species, populations and individuals is the main focus of the burgeoning area of phylogenetics which lies at the interface of molecular biology and computer science and mathematics. Its main objects of interest are phylogenetic tree (these are similar to family trees) and more general graph-theoretical structures called phylogenetic networks (see e.g. i, ii for graduate text books in the area of phylogenetics).
Ever increasing amounts of data have inspired numerous powerful algorithms and deep mathematical insights into how to reconstruct phylogenetic trees and networks from data. However they also indicate that evolutionary relationship between organisms that make up a dataset might be contradictory. By building on recent work by the supervisor and co-workers (iii)–(iv), the project is concerned with developing consensus approaches for phylogenetic networks.
The student will join a world leading group of scientist working at the University of East Anglia, UK. Ideally, the student should be familiar with basic concepts in discrete mathematics such as graphs and should have experience in algorithm development/software engineering. A background in biology is however not required.
Interested students are welcome to contact the primary supervisor informally at [Email Address Removed]