PhD in Infectious Diseases and Complex Systems

Start date: 9 November 2019

End date: 9 December 2019

This is an exciting opportunity for a fully-funded PhD position in data science, collective behaviour and infectious disease epidemiology, not tied to any specific project. This PhD will use ideas from data science, statistics, complexity and network theory to develop new methods that address real-world problems.

An example project:

The network of interactions between co-circulating infections:

Bacteria and viruses often interact with each other in the host competing for resources and space, and have been shown to modify the ability of the other to transmit. Nevertheless, most studies consider considering pathogen species in isolation. Some disease-causing respiratory tract infections are poly-microbial, resulting from synergistic and antagonistic interactions between pathogens. Few of these interactions are well understood, due to the complexity of the system. Moving beyond this requires taking a dynamic, complex systems approach, inspired by analysis of available data. This project aims to develop a data-driven theoretical framework for understanding the ecology of co-circulating infections in human populations. This is a fundamentally inter-disciplinary project that would suit an ambitious student with interests in epidemiology and disease ecology.

The PhD studentship will be awarded to the best candidate and would suit a highly-motivated student with a background in a quantitative subject (e.g. statistics, physics and mathematics) and an interest in public health, or a student with a background in public health or medicine with an interest in quantitative approaches. The ideal candidate will be one who could take the opportunity to shape the topic and direction of the work.