Applied Mathematics

The School of Mathematics is one of the largest integrated schools/departments of mathematical sciences in Europe, with 75 members of academic staff, 21 research staff, and over 140 doctoral students. Over the past few years, the School has been revitalised, strengthening significantly its core capability in mathematical sciences, whilst building strong intra- and inter-disciplinary links, underpinned by an EPSRC platform grant. The School has broad strengths in Algebra, Analysis and Dynamical Systems, Continuum Mechanics, Geometry and Topology, Industrial and Applied Mathematics, Inverse Problems, Mathematical Logic, Mathematical Finance and Actuarial Science, Numerical Analysis and Scientific Computing, Probability and Stochastic Analysis, and Statistics and it’s Applications – many of which have direct relevance to data science.

shutterstock 161234255

Uncertainty Quantification and Data Science

The quantity and complexity of data available to researchers continues to increase rapidly. The group seek to develop the mathematical methods for working with large and / or complex datasets ...

Learn More
shutterstock 281485322

Mathematical Finance and Actuarial Science

Mathematical Finance is a very active branch of both Probability Theory and Applied Mathematics. It is probably one of the few areas in academic research which interact constantly with their field...

Learn More

Probability and Stochastic Analysis

The research in Probability and Stochastic Analysis at Manchester covers a wide range of topics. The group is internationally recognised for its numerous and significant contributions to the theory...

Learn More
data science image 1

Inverse Problems

Inverse Problems typically involve the recovery of some physical characteristics of a material from its response to some excitation such as electromagnetic fields, heat, or mechanical vibrations.

Learn More
shutterstock 175794824

Tropical Mathematics

Tropical methods have applications in a wide range of areas, including combinatorial optimisation and scheduling, microprocessor design, biochemistry, and statistics to name but a few.

Learn More