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We have 17 Mathematical Modelling PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships in Reading
Mathematical Modelling PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships in Reading
We have 17 Mathematical Modelling PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships in Reading
PhD candidates in Mathematical Modelling aim to develop new analytical and computational methods to describe and predict natural phenomena.
What is a PhD in Mathematical Modelling?
Mathematical Modelling is an important part of many academic areas including Biology, Physics, and Computer Science.
Mathematical Modelling PhDs have a focus on the application of analytical and computational methods to describe and predict natural phenomena.
Typical Mathematical Modelling PhDs have a focus on one of the following fields:
- Biostatistics
- Computational Biology
- Financial Mathematics
- Statistical Mechanics
The scope of Mathematical Modelling research can also be divided into theoretical and computational branches.
If your Mathematical Modelling PhD has a theoretical emphasis, you will focus on developing and applying mathematical theories to real-life problems.
If your Mathematical Modelling PhD has a computational emphasis, you will aim to develop new computational methods to describe and predict natural phenomena.
As a PhD student in Mathematical Modelling, you may also choose to study a subject that is distinct from the main focus of your research. This could be the case if your supervisor offers you the freedom to study a subject that interests you independently of the research project.
Typical PhDs in Mathematical Modelling have a duration of 3-4 years.
PhD in Mathematical Modelling entry requirements
In order to be considered for a PhD in Mathematical Modelling, you will need to show that you have the necessary academic background to complete a research project that has a mathematical emphasis.
Depending on the PhD you choose, you will have to show that you are proficient in certain areas of mathematics.
To be accepted into a Mathematical Modelling PhD, you will need to have a relevant undergraduate degree and most likely a Masters with Merit and an overall Upper Second Class honours degree.
Depending on your undergraduate degree, you might also need to have completed some additional modules.
PhD in Mathematical Modelling funding options
In the UK, you can apply for Research Councils doctoral training studentships to do a PhD in Mathematical Modelling.
These are the main sources of funding for PhDs in Mathematical Modelling in the UK.
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Smart control of crop diseases: how can we best combine fungicides and plant resistance genes?
This project would suit a student interested in combining experimentation in the field with mathematical and computational modelling of agri-food biosystems. Read more
Understanding Nonlinear Dynamics of Associative Polymers for Healthcare and Sustainable Applications: Computer Simulations and Mathematical Modelling
Introduction. Associative polymers are macromolecules containing associative groups, also called stickers, that undergo reversible association to physically cross link the polymers into transient networks. Read more
SCENARIO - Modelling the impact of planting choices and management on the delivery of multiple ecosystem services by domestic gardens (SC2023_17)
What we plant and how we manage our gardens can have a significant impact on the environment. Domestic gardens cover up to 30% of UK urban areas, and recent research has linked garden plant characteristics (in terms of their structure and function) with provision of key ecosystem services. Read more
Developing an urban canopy model for improved weather forecasts in cities
Most of the world’s population now experiences an urban version of weather extremes and climate change. Accurate forecasting of weather and air quality in cities relies on correctly representing the physics of turbulent exchange of heat between the surface and the overlying atmosphere. Read more
SCENARIO: Impact of air-sea interactions and deep convection on Mediterranean Cyclones (SC2023_14)
Research Group:
SCENARIO NERC DTP
The Mediterranean basin is among the most cyclogenetic regions in the world and Mediterranean cyclones can lead to devastating socio-economic impacts for coastal communities. Read more
SCENARIO - Strengthening links between agri-environment management and pollination services for cost-effective bee conservation (SC2023_24)
Project. Pollination by bees and other insects is vitally important for UK agriculture, improving production by around £630M. However, despite these benefits, pollinator populations are in decline due to changes in land use, land management and climate. Read more
SCENARIO: Understanding the diversity in the AMOC response to climate change (SC2023_21)
Research Group:
SCENARIO NERC DTP
The Atlantic Meridional Overturning Circulation (AMOC) is a system of currents in the North Atlantic which involves warm water flowing northward in the upper ocean, balanced by a southward ‘return’ flow of cold water at depth. Read more
SCENARIO: Understanding and improving AMOC forecasts in inter-annual to decadal climate prediction (SC2023_22)
Research Group:
SCENARIO NERC DTP
Decadal prediction is a rapidly growing field that forecasts the evolution of regional climate several years to decades ahead by using information from the current state of the climate. Read more
SCENARIO: New space-borne perspectives on the global carbon cycle: untangling role of complex vegetation canopies in novel satellite observations (SC2023_15)
Research Group:
SCENARIO NERC DTP
Understanding the global carbon cycle is of the utmost importance to understanding climate change, and yet our observations of the individual components of the carbon cycle are surprisingly uncertain. Read more
SCENARIO: New approaches to ocean state analysis for climate and forecasting applications (SC2023_43)
Research Group:
SCENARIO NERC DTP
Reconstructing present-day and past ocean temperature salinity and circulation states is critical both to making long-range weather and climate forecasts and for understanding how the ocean has responded over the last century to imbalances in the Earth’s energy budget due to global warming. Read more
SCENARIO: Maximising the value of observational data in ensemble data assimilation for hazardous weather prediction (SC2023_30)
Research Group:
SCENARIO NERC DTP
In a changing climate, an improved ability to forecast hazardous weather is key to the management of risk for society. In weather forecasting systems, large numerical models solve nonlinear equations describing physical processes in the atmosphere. Read more
SCENARIO: Machine learning driven balance relationships for next generation data assimilation systems (SC2023_27)
Research Group:
SCENARIO NERC DTP
Are you fascinated by the complex models and systems that are used to produce weather forecasts? Are you a physicist/engineer/mathematician/meteorologist/computer scientist who would like to work towards a PhD with the Met Office in this important area of scientific endeavour?. Read more
SCENARIO - Moist processes and their interaction with storm tracks (SC2023_09)
Research Group:
SCENARIO NERC DTP
Co-supervisors. Prof. Thomas Spengler, Geophysical Institute, University of Bergen, Norway. Prof. Valerio Lucarini, Department of Mathematics, University of Reading. Read more
SCENARIO - Changes in soil hydraulic properties using long-term innovative monitoring to unveil process dynamics, improve numerical model parameterisation and support Nature-based Solutions (SC2023_41)
This project is based at the UK Centre for Ecology and Hydrology, Wallingford. Read more
Causal Inference Using Modern Econometric Methods
Much of the contemporary empirical economic studies looks to answer specific questions, rather than provide a general understanding of, say, GDP growth. Read more
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