Research Degrees in Computing Science and Mathematics
PhD Studentship Topics
The Department has scope for PhD studies in a number of areas, some of which are discussed below. Funding for studentships is available from time to time. The University is offering some studentships and we may be able to offer a small number of Departmental studentships in 2010. There are, in addition, some SICSA prize studentships available in Computing Science.
If you are interested in applying, please contact the person named in the particular proposal.
Select the appropriate tab below to view all topics, topics relevant to Computing Science, or topics relevant to Mathematics.
Dynamics and Control of Wildlife Diseases
1: Optimal control strategies in disease systems - In particular I have been studying vaccination in domestic dogs in Ethiopia carried out to protect the endangered Ethiopian wolves. In this case there is a high turnover in the dog population and pulse vaccination occurs in villages in geographically widely distributed villages. We will build a theoretical model of pulse vaccination under this scenario and then parameterise it for the system in Ethiopia and look at how frequently we should vaccinate and what the optimal percentage of dogs to vaccinate is. This project scales up from information about individual villages to the entire dog population. This would utilise the biological expertise of project partner Fiona Matthews from Exeter and colleagues in Wildcru at Oxford.
2: Predicting transient disease dynamics and how they might effect disease control strategies - Most models of infectious disease spread look at the long term behaviour of the system and not at the short term dynamics; however, the latter is what is more useful biologically, particularly when investigating control measures. However, studying short term dynamics is more mathematically challenging.
3: Emerging diseases and wildlife reservoirs - Emerging diseases are defined as those which are affecting new hosts or appearing in new geographical areas. It is often the case that these diseases are passed to humans from wildlife due to changes in land use which cause increased contacts between humans and wildlife. It is important to understand how and why diseases emerge and to be able to predict the emergence of new diseases. Determining how to control these diseases is also vital.
4: Models of bumble bee parasites - Stirling is the home of the Bumblebee conservation Trust and this project would make use of this fact and the expertise that we have here. The first part of the project would look at the available data and model the dynamics of a parasitic infection within a nest, we will then change scales and look at how to use the single nest model to determine between nest transmission and the population level impact of parasites on bumblebee populations. This is an important problem as bumblebee populations are declining and they are important pollinators of our agricultural crops.
Evolutionary and ecological systems
1: Control strategies in multi-host and shared pathogen systems - Biological systems where several host species share a common disease (for example, both cattle and badgers are vulnerable to Bovine TB, or those that cross from wildlife to human) is widespread, and with climate change and globalisation this is becoming an increasing problem. Here control (eradication) of the disease can be critical, however developing a strategy can be difficult. Problems may include situations where controlling (e.g. culling) all the species is not a viable option and so the question arises as to whether the disease can be removed from the system by only controlling a select number of host species. In addition, these problems naturally extend into optimisation problems with an aim of, for example, minimising the number of individuals culled/vaccinated or minimising the total cost.
2: Co-Evolution of Mating Conflict - Natural selection drives the evolution of species towards an optimum state with respect to their current environment. However sexual conflict over mating can often shift species from such optima as individuals attempt to gain their own way during reproductive encounters. Traits that evolve through sexual conflict can reduce the fitness of the opposite sex. For example, males can harass females into accepting unwanted and costly matings; in response females develop both morphological and behavioural traits that enable them to resist unwanted copulations. This antagonistic co-evolution of male and female traits can result in the exaggeration of traits that reduce the fitness of the species as a whole. The studentship will be in collaboration with School of Biological and Environmental Sciences and involve developing established models of co-evolution so that empirical data can be easily entered into them to test their robustness and gain new insights into sexual conflict, natural selection and their interaction.
