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Applied Mathematics PhD Projects, Programmes & Scholarships

We have 397 Applied Mathematics PhD Projects, Programmes & Scholarships

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We have 397 Applied Mathematics PhD Projects, Programmes & Scholarships

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Tropical Optimization

Tropical algebra is linear algebra developed over the max-plus semiring (extended real line endowed with tropical addition `a+b'max(a,b) and tropical multiplication `ab'a+b). Read more

Genetics of skin cancer

  Research Group: Statistical Genetics
BACKGROUND. Genetics, together with sun exposure, play an important role in the development of skin cancers. Our lab studies both melanoma and the keratinocyte cancers basal cell carcinoma and squamous cell carcinoma. Read more

Parallel-in-time and consistent training methods for solving hyperbolic PDEs via physics informed neural networks

In recent years, neural networks (NNs) have been applied in various fields of numerical modelling to learn solutions of mathematical models from data rather than by approximating equations and solving them by standard numerical methods. Read more

Multidimensional localised patterns in fluids

Spatially localised behaviour occurs in a wide range of fluid problems from water waves to convection. In this project we would use a combination of analytical and numerical methods to investigate the emergence and properties (e.g. Read more

Design of Experiments: estimation of selected interactions in factorial experiments

Experiments with factorial treatment structure are used widely in industrial experiments and have applications in many other areas, including medical research and the horticultural and agricultural industries. Read more

Mathematical models for the characterisation of the dynamics of biological systems

Biological systems are constantly exposed to changing environments and adapt to them. That is, biological systems are capable of gathering information about their environments and processing them. Read more

Ensemble-based inference of multi-dimensional Hawkes process driven by count data

The vision of this research is to develop a novel sequential inference method for constructing a large-scale influence network from spatio-temporal count data, which could encompass an arbitrary number of events in a time interval, both as a batch and real-time data stream. Read more

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