Within mathematical sciences we study questions of a mathematical character, either from a purely theoretical perspective or directed towards practical applications. In either case, the mathematical problem and its properties is the main focus. The research is based on mathematical proofs and/or computer-assisted calculations.

Picter of stones in diffrent foramtions Photo credit Sergey Galushko

Doctoral studies in Mathematical Sciences are offered by the Department of Mathematics (MAI), and the Department of Science and Technology (ITN). Mathematical Sciences comprise the following subject areas:

Computational Mathematics 

Computational Mathematics is about the development and analysis of numerical methods and algorithms to solve mainly technical and scientific problems, formulated as mathematical models. Our research group in this area is successfully examining numerical methods for use on time-independent partial differential equations.


Mathematics is conducted in fields such as algebra, discrete mathematics, dynamic systems, functional analysis, inverse problems, mathematical physics, partial differential equations, and topology.

Mathematical Statistics

Mathematical Statistics is dedicated to probability theory and statistical inference theory. We are skilled in theoretical probability theory and multivariate statistics.


Optimisation deals with theories and methods to analyse and solve mathematical decision problems. In general optimisation, MAI has one of the most prominent groups in Sweden, with extensive experience in practical optimisation and a well-balanced mix between mathematics and applications.

Interdisciplinary Mathematics

Interdisciplinary Mathematics covers research which involves two areas. The main area is within mathematical sciences (computational mathematics, mathematics, mathematical statistics, or optimisation), and the other is an area outside mathematical sciences, involving subjects such as physics, biology or medicine.

Teaching is based on lectures, seminars, group work and supervision. You are expected to actively participate in seminars, guest lectures and conferences.

Doctoral studies in mathematical sciences prepare for a continued academic career involving research and teaching as well as for a professional life outside the academic world. Mathematical breadth and depth, and the ability to absorb new theory and digest complex events are in high demand across a large part of the labour market. PhD-level mathematicians are wanted in IT security, cryptology, resource optimisation, simulations for example in pharmaceutical development, autonomous systems, risk analysis in finance and insurance, meteorology, communication systems, and many other areas.

The impending future challenges, not least concerning sustainable development and climate transition, require significant mathematical expertise, both directly for example in optimisation, mathematical modelling, and dynamical systems, and indirectly in that all relevant science and technology developments rely on a mathematical framework.

In order to join us as a student, you must have a keen interest in mathematics, regardless of which field you wish to specialise in. All available positions are published on Linköping University’s Vacancies page. Use the dropdown menus to filter according to department and profession.

Vacancies page

Study syllabus Mathematical Sciences

General study syllabus for Mathematical Sciences (PDF)

Research school in Interdiciplinary Mathematics

PhD in Mathematics?

Doctoral studies at Linköping University

Current research projects in Mathematics

Group picture of Nageswari Shanmugalingam, Anders Björn, Jana Björn and Tomas Sjödin.

Nonlinear Potential Theory

The research group is mainly interested in analysis on metric spaces, and in particular nonlinear potential theory associated with p-harmonic functions and quasiminimizers in Euclidean and metric spaces.

Reflection in the water.

Differential Equations and Analysis on Metric Spaces

Differential equations describe many real-world phenomena but can rarely be solved exactly. We therefore study properties of their solutions in other ways, in very general situations, similarly to creating an identikit of an unknown criminal.

Abstract 3D pattern.

Modern Multivariate Statistical Analysis

Nowadays there is a great need to analyse complex high-dimensional data. Modern theories must be developed through the knowledge of the classical methods of multivariate statistics.

Contact Doctoral studies in Mathematical Sciences