The ongoing COVID-19 pandemic has witnessed the generation of over 150,000 genomes of the causative agent, the virus SARS-CoV-2, across the globe. To date, the focus of most genomic studies has been at the population level, i.e. on genetic changes observed in the viral consensus genome which represent the dominant variation within infected individuals. Although such data has been key to understanding the spread and evolution of the virus, the intra-host evolutionary dynamics of SARS-CoV-2 remain poorly understood.

The aim of this PhD project is to utilize publicly-available raw sequencing datasets (Amplicon and RNA-Sequencing data) to understand the full underlying within-host diversity of the virus and its potential impact on transmission, pathogenesis and vaccine design. Specifically, this project will use phylogenetic methods to evaluate (1) whether SARS-CoV-2 within-host diversity can provide further resolution for identifying transmission clusters and (2) whether any inferences on the direction of transmission can be made with high statistical support, as is done for other viruses. To gain further insights into how SARS-CoV-2 within-host dynamics affects which viral variants are transmitted, we will search for genomic signatures of transmission from known households and outbreaks and explore whether factors such as host’s age, sex, geographical location, infection status (asymptomatic, symptomatic) and clinical outcome are related to viral genetic diversity.

Applicants should have prior experience with viral sequence data, bioinformatics and a knowledge of molecular evolution is preferred. Technical expertise with at least one computer coding language (ideally python or R) is also highly desirable.