Master's Programme in Engineering, with specialisation Engineering Mathematics, 300 credits

In autumn 2026, Uppsala University will launch a five year Master’s Programme in Engineering, with specialisation Engineering Mathematics. The programme complements the existing range of engineering programmes and fills a valuable niche that is currently missing. Mathematics plays a key role in today’s high-tech and digitised world, and the applications of advanced mathematics are expanding across all sectors of society as technological development accelerates.

The official programme page will be published in mid-October, alongside the full listing of the university’s degree programmes for the 2026/2027 academic year. Below is a preliminary introduction to the programme, including the curriculum.

A Master of Science in Engineering in Applied Mathematics is needed to meet today’s challenges and to drive tomorrow’s innovation. In a world shaped by digitalisation, automation, and artificial intelligence, mathematics is at the core of understanding and shaping the rapidly evolving technological landscape. By combining in-depth mathematics with broad technical knowledge, the programme will educate engineers who are equipped to address the most complex problems facing industry.

This programme is not only an investment in students' futures, but also a necessity for maintaining the competitiveness of Swedish industry. By training a steady stream of highly qualified engineers who can integrate mathematical principles with advanced computer science and AI-based technologies, we ensure that companies and organisations can continue to innovate and create value in an increasingly data-driven and technology-oriented world. One major challenge many industries face is applying modern AI to critical problems, and there is a general shortage of professionals on the labour market with the necessary depth of mathematical expertise.

The need for applied mathematicians extends far beyond AI and industrial applications. Their skills are also in demand in sectors such as insurance and finance, where advanced mathematical modelling is used to value financial instruments and assess risk. They also play an important role in interdisciplinary fields such as life sciences and the social sciences.

Profiles and course packages

During the final two years of the programme, students will have the opportunity to tailor their studies according to two profiles: Data Analysis and AI and Modelling, Simulation and Control. These specialisations allow students to deepen their knowledge in two fields that play a central role in modern technological development, making them highly attractive in a labour market with a strong demand for such expertise. The study paths within the profiles are not mandatory; students are free to combine courses in other ways to create their own unique engineering profile. In particular, the programme also offers two optional course packages, one in Financial Mathematics and one in Life Sciences, for students who wish to pursue a specialisation in these areas.

Preliminary Study Outline

Semester 1

Introduction to Applied Mathematics, 5 credits
Single Variable Calculus, 10 credits
Linear Algebra I, 5 credits
Comupter Programming I, 5 credits
Linear Algebra II, 5 credits

Semester 2

Mechanics, 10 credits
Multivariable Calculus, 10 credits
Probability Theory I, 5 credits
Electromagnetism I, 5 credits

Semester 3

Comupter Programming II, 5 credits
Inference Theory I, 5 credits
Introduction to Scientific Computing, 5 credits
Complex Analysis, General Course, 5 credits
Fourier Analysis, 5 credits
Mathematical Modelling and Problem Solving, 5 credits

Semester 4

Control Engineering I, 5 credits
Technical Thermodynamics, 5 credits
Industrial Economics, 5 credits
Ordinary Differential Equations I, 5 credits
Scientific Computing for Data Analysis, 5 credits
Groups and Discrete Mathematics, 5 credits

Semester 5

Probability Theory II, 5 credits
Algorithms and Data Structures I, 5 credits
Introduction to Stochastic Processes with Applications, 5 credits
Optimisation Methods, 5 credits

Students select either the following course package:

Graph Theory, 5 credits
Complex Networks, 5 credits

or:

Real Analysis, 10 credits

Semester 6

Perspectives on Mathematics, 5 credits
Regression Analysis, 5 credits
Independent Project in Applied Mathematics, 15 credits

Elective courses:

Mechanics III, 5 credits
Fluid Mechanics, 5 credits
Algorithms and Data Structures II, 5 credits
High-Performance Computing, 10 credits
Statistical Machine Learning, 5 credits
Partial Differential Equations, Introductory Course, 5 credits

Profile: Data Analysis and AI

Semester 7

Introduction to Data Analysis, 10 credits
Large Language Models and the Social Impact of Artificial Intelligence, 5 credits
Topological Data Analysis, 5 credits

Students have the option to study the following finance package:

Probability Theory and Martingales, 10 credits
Financial Theory, 5 credits

or:

Probability Theory and Martingales, 10 credits
Financial Derivatives, 7.5 credits

Elective courses:

Advanced Probabilistic Machine Learning, 5 credits
Categorical Data Analysis, 5 credits
Database Technology I, 5 credits
Computer-Intensive Statistics and Applications, 10 credits
Statistical Machine Learning, 5 credits
Generalised Linear Models, 5 credits

Semester 8

Foundations of Data Analysis, 10 credits
Deep Learning, 5 credits
Reinforcement Learning A, 5 credits

Elective courses:

Data Engineering I, 5 credits
Robotics, 10 credits
Statistical Machine Learning, 5 credits
Markov Processes, 10 credits
Time Series Analysis, 10 credits
Data Engineering II, 7.5 credits
Parallel and Distributed Computing, 5 credits
Data Mining I, 5 credits

Semester 9

Data, Ethics and Law, 5 credits
Data Security and Privacy, 5 credits
Project in Applied Mathematics, 15 credits

Students have the option to study the following Life Sciences package:

Modelling of Biological Systems, 7.5 credits
Pharmaceutical Bioinformatics with Sequence Analysis, 7.5 credits

Elective courses:

Accelerator-Based Computing, 5 credits
Data Mining II, 5 credits
Specialisation in Data Analysis, 5 credits

Semester 10

Master's Thesis in Applied Mathematics, 30 credits

Profile: Modelling, Simulation and Control

Semester 7

Control Engineering II, 5 credits
Scientific Computing for PDEs, 5 credits
Applied Finite Element Methods, 5 credits
Applied Systems Analysis, 5 credits

Students have the option to study the following finance package:

Probability Theory and Martingales, 10 credits
Financial Theory, 7.5 credits
Financial Derivatives, 7.5 credits

Elective courses:

Partial Differential Equations, 10 credits
Differential Topology, 10 credits
Differential Geometry, 10 credits
Quantum Physics, 10 credits
Signal Processing, 10 credits
Applied Mathematics, 5 credits
Database Technology I, 5 credits
Statistical Machine Learning A, 5 credits
Generalised Linear Models, 5 credits
Electromagnetism II, 5 credits

Semester 8

Applied Dynamical Systems, 5 credits
Modelling of Complex Systems, 10 credits

Elective courses:

Data Engineering I, 5 credits
Robotics, 10 credits
Mechanics III, 5 credits
Deep Learning, 5 credits
Markov Processes, 10 credits
Lie Groups, 5 credits
Control System Security, 5 credits
Principles of Quantum Computers and Quantum Programming, 5 credits
Statistical Machine Learning, 5 credits
Time Series Analysis, 10 credits
Functional Analysis, 5 credits
Parallel and Distributed Computing, 5 credits
Data Mining I, 5 credits

Semester 9

Data, Ethics and Law, 5 credits
Data Security and Privacy, 5 credits
Project in Applied Mathematics, 15 credits

Students have the option to study the following Life Sciences package:

Modelling of Biological Systems, 7.5 credits
Pharmaceutical Bioinformatics with Sequence Analysis, 7.5 credits

Elective courses:

Partial Differential Equations, 10 credits
Advanced Numerical Methods, 10 credits
Control Engineering III, 5 credits
Analytical Mechanics, 5 credits
Partial Differential Equations, 10 credits
Data Mining II, 5 credits
Specialisation in Data Analysis, 5 credits

Semester 10

Master's Thesis in Applied Mathematics, 30 credits

Contact

If you have any questions about the programme, you are welcome to contact any of the following persons:

Jordi-Lluís Figueras, Programme Director and head of the working group that developed the programme
Martin Herschend, Subject Coordinator in Mathematics
Georgios Dimitroglou Rizell, Head of the Department of Mathematics