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We have 22 University of Birmingham, School of Mathematics PhD Research Projects PhD Projects, Programmes & Scholarships

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School of Mathematics  University of Birmingham

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University of Birmingham, School of Mathematics PhD Research Projects PhD Projects, Programmes & Scholarships

We have 22 University of Birmingham, School of Mathematics PhD Research Projects PhD Projects, Programmes & Scholarships

Empirical Modeling in Financial Engineering

This project explores the decvelopment and application of empirical techniques in Financial Engineering. If you are interested, then please complete an application to the PhD in Applied Mathematics. Read more

Mathematical Modelling: Real Estate Finance and Investment

Many mathematical constructs exist within the real estate finance and investment universe. This project seeks to explore, develop and refine these models to yield meangingful insights. Read more

Financial Engineering: Modelling and Methods

This project will explore the utility of various mathematical models within common financial instruments. If you are interested, then please complete an application to the PhD in Applied Mathematics. Read more

Differential equation modelling to address male infertility

Infertility affects 1 in 6 couples, is emotionally devastating, and requires expensive and invasive treatments. Importantly, we place a significant and unequal burden on women, who often require risk-bearing procedures to address what is caused by, in 50% of cases, a male factor. Read more

Statistical inference for epidemics models

Mathematical models have been established as an important tool for capturing the features that drive the spread of a disease, predicting the progression of an epidemic and guiding the development of effective control strategies to prevent potential outbreaks. Read more

Mathematical Machine Learning for Molecular Modeling

Project description. This PhD project aims to develop Machine Learning methods for Molecular Modeling with a particular focus on aspects relevant to dynamics preserving coarse-graining strategies. Read more

Modelling Convergent, Divergent and Oscillatory Phenomena in Social Dynamics

If you are interested in building mathematical models to explain social phenomena in a variety of contexts, from flocking animals to interacting crowds, and you have a strong academic background in applied mathematics or a related discipline, then this project could be perfect for you. Read more

Funded PhD Opportunity: Pioneering Time Series Analysis Through Self-Normalisation

About the project. Techniques and Overview. In the intricate world of statistical analysis, accurately understanding the variance of temporally correlated data is crucial for reliable conclusions. Read more

Mathematical analysis of PDEs arising from modelling biological processes

Biological systems, in contrast to physical systems, exhibit a high level of complexity. Attempting to replicate their dynamics through mathematical models (system of differential equations) turns out to be quite challenging. Read more

Heads and Tails - Tracking the sperm's beating flagellum

Infertility affects 1 in 6 couples, is emotionally devastating, and requires expensive and invasive treatments. Importantly, we place a significant and unequal burden on women, who often require risk-bearing procedures to address what is caused by, in 50% of cases, a male factor. Read more

Data-driven modeling for crowd dynamics

Predicting the behaviors of pedestrian crowds is of critical importance for a variety of real-world problems. Data driven modeling, which aims to learn the mathematical models from observed data, is a promising tool to construct models that can make accurate predictions of such systems. Read more

Data driven approaches for nonlinear inverse problems

The project aims to develop new techniques for solving complex inverse problems that arise in various scientific fields. In many real-world applications, such as medical imaging, geophysics, and material science, we often seek to recover the hidden properties of a system from indirect and noisy measurements. Read more

Neural Networks for Complex Dynamical Systems

Details. Dynamical systems are often solved/integrated by a suitable numerical discretisation method in such a way that certain properties of the underlying systems will be preserved. Read more
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