Advice on choosing a PhD

• Find an area of research that excites you, and where you have the necessary skills. The examples below will give you some ideas of the type of project that interest staff in the Zeeman Institute; but we are all open to new ideas or suggestions.
• Contact the member of staff, arrange a visit to Warwick (if possible) and talk to other students about their experiences.
• Together with your potential supervisor, find the best way to enter the Warwick PhD system and obtain funding.

Epidemiology: a quantitative approach to surveillance for tree pests and diseases.

Stephen Parnell (Life Sciences) and collaborators at Forest Research

Introductions of invasive tree pests and diseases are rising, inflicting severe economic and environmental consequences. Swift and efficient surveillance for early detection is essential for enabling eradication or cost-effective control measures. Surveillance typically relies on a diverse group of observers, ranging from members of the public to trained inspectors. Additionally, pests and diseases exhibit variation in their signs and symptoms, impacting the ease with which they can be spotted. While diagnostic sensitivity in the laboratory is routinely quantified, there is a critical factor often overlooked: the probability of an observer detecting the pest or disease in the first place, often known as ‘sampling effectiveness’. Quantifying sampling effectiveness is crucial in answering essential questions such as the likely prevalence of a pest or disease when initially discovered and how frequently and intensively searches need to be conducted to detect a pest or disease before it gets out of control. The project is a collaboration with Forest Research and the successful student will also benefit from the involvement of Defra Plant Health.

Applications are open here. Please get in touch first for more info.

Required skills: strong quantitative training

Mathematical/Statistical Biology: using data to build models of chromsome movements during human cell division.

Nigel Burroughs (Mathematics) and collaborators in WMS

Cell division is a complex process where 2 near identical cells are created, in particular each cell receiving a copy of the chromosomes. The cell achieves this feat by building a mechanical machine called the spindle that captures and separates the copied chromosomes with high fidelity. We have built a number of dynamic models for phases in this process and fitting them directly to experimental data generated in WMS. This has given us unique insight into this complex self organising and error correcting process. The project could be on the model analysis side, analysing the bifurcation structure of models, or more data driven aspects, building models and inference algorithms. We work at multiple spatial and time scales.

Required skills: strong quantitative training (eg in sDEs, dynamical systems), programming skills in MatLaB, python, R or C++ is advised, Bayesian computational statistical methods useful.

Epidemiology: Controlling measles outbreaks in the UK.

Matt Keeling (Maths & Life Sciences) and Ed Hill (Maths)

Measles was a common disease and caused substantial loss of life before the roll-out of vaccination in the 1970s. In recent years, the uptake of measles (MMR) vaccine in many areas has fallen sharply, leading to fears that there is a build-up of susceptibility in the population. This project will investigate the potential for future localised outbreaks and the cost-effectiveness of the current vaccination programme. We will also focus on the implications of systemic loss of immunity following measles infection.

Required skills: strong quantitative training.

Epidemiology: Quantifying the impact of highly pathogenic avian influenza in the UK wild bird population.

Ed Hill Link opens in a new window(Maths), Erin GorsichLink opens in a new window (Life Sciences), Mike TildesleyLink opens in a new window (Maths & Life Sciences) and Matt KeelingLink opens in a new window (Maths & Life Sciences)

Highly Pathogenic Avian Influenza (HPAI) has long been associated with substantial outbreaks and losses in poultry farms, with occasional spill-over into human populations – although, fortunately there is limited evidence of transmission between humans. Wild waterfowl are well documented reservoirs, and since 2022 there has been an unprecedented decline in many wild bird populations driven by HPAI (seabird colonies most affected). Quantifying the spread and impact of HPAI is a necessary first step in the conservation of the UK wild bird populations. Fortunately, the UK has extensive population records collected by professional and amateur ornithologists that can aid such efforts. This project will collate the available data to investigate the potential impact of HPAI in wild bird populations since 2022, develop projections and model the prospective impacts of conservation practices intended to mitigate HPAI infection risk.

Required skills: strong quantitative training, programming skills advised.

Epidemiology: Modelling the spread and control of highly pathogenic avian influenza in poultry and quantifying zoonotic transmission risk.

Mike TildesleyLink opens in a new window (Maths & Life Sciences) and Ed Hill Link opens in a new window(Maths)

In recent years, cases of Highly Pathogenic Avian Influenza (HPAI) H5N1 in poultry have been increasing worldwide and this, combined with the recently reported cases of H5N1 in mammalian species and sporadically reported human cases, has raised concerns regarding the potential for sustained zoonotic transmission to occur over the coming years. This project will build upon previous work that has been carried out on modelling the spread of HPAI H5N1 in South and South East Asia, as well as recent work in the UK, to establish the ongoing risk of HPAI to domestic poultry farms both in the UK and in other countries and the potential for zoonotic transmission to occur. The project will be carried out in collaboration with the Animal and Plant Health Agency (APHA) as well as relevant international veterinary agencies to provide timely advice to minimise the future impact of HPAI.

Required skills: strong quantitative training.