Numerical analysis and scientific computing
Our researchers develop and analyse algorithms that compute numerical approximations and apply them to realworld problems.
PhD projects
We welcome applications for PhD study in all areas of mathematics in the life sciences.
PhD enquiries related to this theme can be directed to Dr Joel Daou.
Numerical analysis is the branch of rigorous mathematics that concerns the development and analysis of methods to compute numerical approximations to the solutions of mathematical problems. It is a broadly based discipline that sits at the interface between mathematical analysis and scientific computing.
Scientific computing describes the use of numerical simulation to study natural phenomena, complementing the more traditional experimental and theoretical approaches. Another broad discipline, it spans all the sciences with strong links to numerical analysis, computer science and software engineering.
Our work covers the breadth of these disciplines from fundamental theory and algorithm development through to implementation in open source software. Our researchers have expertise in the following areas.
Areas of expertise

Approximation theory
Approximation theory is a key component of contemporary algorithms used in computational science and engineering.
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Numerical linear algebra
Numerical linear algebra is at the heart of computational algorithms used in science and engineering, and in industry.
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Scientific computing
Scientific computing is the study of the techniques that underpin disciplinespecific fields of computational science.
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Uncertainty quantification
Uncertainty quantification is a modern interdisciplinary science that cuts across traditional research groups and combines statistics, numerical analysis and computational applied mathematics.
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Research outputs
Find the Department's recent publications in the University's database.
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Postgraduate research
Discover the PhD opportunities available in the Department of Mathematics.
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Research seminars
Research seminars on topics associated with numerical analysis and scientific computing take place regularly in the following series: