Dr Mirela Domijan
Exploring the effects of light and temperature on the plant circadian clocks
Plants need to co-ordinate a myriad of developmental, metabolic, and physiological processes every day in response to daily light and temperature changes. They need to be robust to small stochastic fluctuations in their environment, but also be attuned to and respond correctly to bigger changes. I am interested in exploring the effects that temperature and light have on the circadian clock, an important timekeeper which allows aforementioned processes to be executed in a timely manner. The project proposed here will build on work done in collaboration with Dr Benedicte Wenden (INRA- Bordeaux). Good start can be made with the following review: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516730/
Models of mammalian circadian clocks and chronotherapy
Chronotherapy has been gaining momentum in recent years as timing of drug administration and even vaccinations can influence efficacy and toxicity.
Together with Dr Vanja-Pekovich Vaughan (at the Institute of Life and Medical Sciences) I am looking at the effect of inflammation on the circadian clock and the effect of specific drugs on the clock rhythms. Good starting can be made with the following review: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375788/
Dr David Haw
Responding to and preventing zoonotic outbreaks – consolidating economics, virology, and network science to build holistic viral outbreak mitigation strategies
The 2003 Midwest outbreak of Mpox was caused by trade of wild animals. Lumpy Skin Disease Virus (LSDV) outbreaks usually result in movement control and cessation of trade. We will model similar and potential emerging poxvirus outbreaks, their likely life and economic burden, and the effectiveness and optimisation of mitigation strategies.
Dr David Lewis
The influence of turbulence on plankton population dynamics
The objective of this project would be to try and develop new population models, which, for the first time, will seek to include the effects of the local turbulent environment. To a certain extent this is made easier by the very small size of a typical plankton, which ensures that on the scale of an individual plankton the turbulence can be assumed to be homogeneous and isotropic. However, one objective would be to examine how much larger scale features of the turbulent flow influence the development of a large population of an individual species. This would be done by building upon existing plankton population models in the literature, combined with a working model of the turbulent flow field.
Other projects offered are: The influence of prey distribution on plankton predation, The role of wave induced Coriolis-Stokes forcing on the wind driven mixed layer
Dr Emily Nixon
Dr Nixon is currently on leave. Nixon group builds and analyses mathematical, statistical, and computational models of infectious disease outbreaks, within a One Health framework (the interconnection between humans, animals and their shared environment). They use models to understand fundamental epidemiological processes and as predictive tools, to improve global health and welfare. Their work is fundamentally interdisciplinary, and they work closely with experimental scientists, as well as industry and policymakers, to ensure that their work has the greatest impact.
Dr Chris Overton
Infectious Disease Surveillance
During outbreaks of infectious diseases, surveillance plays a key part of the public health response. However, the data are often biased and disease trajectories are uncertain. Mathematical modelling can play a key part in supporting the surveillance effort. Some of the key contributions mathematics can offer are nowcasting, which aims to quantify uncertainty in the current dynamics; forecasting, which predicts how the dynamics are expected to change in the future; and parameter estimation, where estimating baseline epidemiological quantities is useful for informing public health interventions.
Time delay distributions in infectious disease data
Time delay distributions inform the majority of transitions between different states during an epidemic. However, estimating these in real-time suffers from multiple biases due to the shape of the epidemic curve. These biases have further consequences on other epidemiological parameters, such as the severity of infection. Improving our theoretical understanding of these dynamical biases in time delay distributions is essential for developing robust tools for infectious disease surveillance.
Stochastic population dynamics in structured populations
Real-world populations typically exist within some form of population structure, often represented using a network. Dynamical systems acting on these populations, such as infectious disease spread or evolutionary dynamics, will be affected by the structure imposed on the population. Investigating the influence of population structure can shine a light on how these dynamical systems might affect real populations. For example, certain network structures may amplify the spread of an advantageous mutant, speeding up the evolutionary process, or other structures might increase the speed at which an infectious disease spreads.
Antimicrobial resistance
At the interface between evolution and epidemiology sits a key public health problem - antimicrobial resistance (AMR). Using modelling techniques from ecology, evolution, and epidemiology, we can improve our understanding of AMR.
Healthcare pressures
Infectious disease outbreaks add immense pressure to local public health infrastructure, such as hospitals and primary care providers. Understanding the relationship between community prevalence and healthcare pressures is essential for guiding an efficient public health response. Using a combination of methods from forecasting, survival analysis, and causal inference, mathematical modelling can play a key role in improving our understanding in this space.
Professor Kieran Sharkey
Applied epidemiology/ population dynamics
Mathematical modelling to gain insights into the spread of epidemics in real systems such as livestock industries and humans.
Mathematics of networks
Developing mathematical approaches to understand and control the dynamics on and of networks.
Bakhti Vasiev
Mathematical modelling of embryogenesis
This PhD project is devoted to mathematical study of the mechanisms of differentiation and migration of cells taking place during embryogenesis. The main paradigm here is that there are biochemical substances (morphogens), which are produced/decayed at different rates in different cells, form concentration gradients. The concentration of morphogens in turn cause differentiation and migration of cells and results to formation of different tissues. The evolution of the entire system is driven by feedback mechanisms and this project is about identifying feedback loops involved in development of embryonic tissues. The project involves development of models, represented by partial differential equations, analysis of these equations and programming in C++/Matlab for numerical integration of model equations.
Pattern formation in excitable systems with applications to developmental biology
Excitable media are characterized by homogeneous steady state, where over-threshold disturbances can result to formation of propagating waves or localized structures. Both types of solutions are important for mathematical studies in developmental biology. This project is devoted to the analysis of solutions, their types and bifurcations in models describing excitable dynamics. This research has various applications in developmental biology and can, for example, be used for a general explanation of developmental processes in populations of unicellular organisms.
Spatio-temporal dynamics in heterogeneous populations of interacting bacteria
This project is focused on mathematical studies of interference competition between growing bacterial populations. The outcome of such competition is commonly manifested by spatial distribution of bacteria and reflect such phenomena as prevention of colonisation, displacement of the competitor or coexistence in spatially separated patches. The project involves development of models, discrete (represented by cellular automata) as well as continuous (represented by systems of partial differential equations). Continuous model are used to reveal general conditions which should be satisfied for one of populations to take over or for their coexistence. Discrete model will be used for the analysis of cellular events in smaller populations (i.e. up to 105 bacteria) where behaviour of each bacterial species and its interactions will be modelled by phenomenological rules. The project aims a design of medical treatment based on competition between toxic/nontoxic bacteria as well as understanding biophysical mechanisms of biofilm formation.
Mathematical modelling of the dynamics of aging and mortality in human populations
This project is focused on mathematical analysis of mortality data for human populations and development of mechanistic models of aging reproducing these data. In this project we consider human population as consisting of subpopulations with different aging and mortality characteristics and the latter being affected by stochastic factors. The role of heterogeneity and stochasticity on the net rate of mortality is studied by means of mathematical modelling and analysis. Mechanistic models of aging will be represented by differential equations with stochastic terms. These models will be studied analytically and integrated numerically using C++/Matlab programming. The project aims an impact to the improvement of policies and medical services for an increase of lifespan in human populations.
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