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Mathematics PhD Research Projects

We have 317 Mathematics PhD Research Projects

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We have 317 Mathematics PhD Research Projects

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Developing a methodology to measure and optimise the impacts of climate change on urban building environment

Following the Government heating and energy target guidelines to improved building performance it is important to consider building design and human activities when examining the impact of changing microclimate due to climate change. Read more

Random dispersive and wave equations

The central theme of this project is the mathematical analysis of nonlinear dispersive partial differential equations (PDEs), such as the nonlinear Schrödinger equations (NLS) and the nonlinear wave equations (NLW). Read more

Towards better representation of surface-subsurface flow interactions in urban areas particularly during extreme events

Detailed flood models are increasingly used to assess future flood risk in cities and catchments, and to design flood attenuation features including green infrastructure (GI) which reduce the amount of water entering drainage systems via infiltration, transpiration and storage. Read more

Dynamic Pricing and Learning

Main research aims. This project is on dynamic pricing and learning. statistical learning combined with price optimization. The precise content will depend on a survey of key literature and the strengths and interest of the research team. Read more

Nonlinear wave description of glacial outburst floods

Glacial outburst floods, or jökulhlaups, are a major hazard in many actively glaciated regions. They can be generated by a wide range of mechanisms such as ice-dammed lake drainage, glacier surges and subglacial volcanic activity. Read more

Dynamical system approaches for solving variational inequalities

Variational inequalities (VIs) are a powerful mathematical model which unifies important concepts in applied mathematics like systems of nonlinear equations, necessary optimality conditions for optimisation problems, complementarity problems, obstacle problems, or network equilibrium problems. Read more

Efficient methods for solving clustering-with-hyperplane problems

Clustering is one of the central problems in machine learning. In its classical paradigm, the clustering problem asks for partitioning a given dataset into k clusters in such a way that the distance between each point and the centroid of the corresponding cluster is minimized. Read more

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