Numerical analysis and scientific computing
Our researchers develop and analyse algorithms that compute numerical approximations and apply them to real-world problems.
We welcome applications for PhD study in all areas of numerical analysis and scientific computing.
PhD enquiries related to this theme can be directed to Dr Stefan Güttel.
We design algorithms for the solution of continuous problems, which requires the development of numerical approximations when closed form solutions do not exist. These continuous problems can arise from mathematical models of physical processes such as fluid flow, heat transfer and solid mechanics. We also treat finite-dimensional matrix problems, which typically arise from discretization of continuous operators or from data-driven applications.
Our work covers the whole spectrum of the discipline from fundamental theory to algorithms to implementation in open source software.
Our research focuses particularly on
- Approximation theory
- Fast solvers for partial differential equations
- Finite element approximation
- Numerical algorithms and software development
- Numerical linear algebra
- Uncertainty quantification for partial differential equations
We have close links with international companies such as Arup, NAG, and The MathWorks.
Areas of expertise
Approximation theory is a key component of contemporary algorithms used in computational science and engineering.
Numerical linear algebra
Numerical linear algebra is at the heart of computational algorithms used in science and engineering, and in industry.
Scientific computing is the study of the techniques that underpin discipline-specific fields of computational science.
Uncertainty quantification is a modern inter-disciplinary science that cuts across traditional research groups and combines statistics, numerical analysis and computational applied mathematics.
Our staff, students and postgraduate researchers have access to a fantastic range of facilities across the University.
Find the Department's recent publications in the University's database.
Discover the PhD opportunities available in the Department of Mathematics.