Mathematics, Statistics and Data Science, MSc

120 creditsMaster
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Overview

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Educational area:
Engineering Physics and Mathematics
Degree:
Master of Science, MSc
Language:
English
Duration:
2 years
Rate of study:
Full-time, 100 %
Instructional time:
Daytime
Information about tuition fees

Important dates

Application opens:
Application closes:

Summary

Mobile networks, financial markets, search engines, climate models and AI. Critical systems like these rely on mathematical foundations that most people never consider. This programme trains you to identify, analyse, and solve complex problems using mathematics, statistics, and computational methods, preparing you to develop innovative solutions in modern industry and research.

Specialisations

A specialisation lets you focus your studies within a specific area. You gain in-depth knowledge and skills that prepare you for a successful career.

Foundations of Machine Learning and AI

Understand machine learning and AI from their mathematical foundations.

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Mathematical Statistics

Gain deep expertise in the theory and methods of statistical inference, probability, and data analysis.

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Mathematical Finance

How do modern trading houses and global markets use and apply complex mathematics? Discover the systems that underlie modern finance, and explore how these are transforming with advances in AI.

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Computational Biology

Apply mathematical and computational methods to biological systems, from gene networks and metabolic pathways to evolutionary dynamics and ecology.

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Engineering and Computational Mathematics

Develop the mathematical tools used to model and solve complex problems in engineering and the physical sciences.

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Theoretical Mathematics and Mathematical Physics

Pursue mathematics at its most fundamental, studying the structures and theories that underlie the entire discipline.

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Programme description

You begin by building a shared foundation in areas like high-performance computing, computer programming, statistical inference and nonlinear optimisation. Following this foundation, you can branch into a number of specialisations, covering theoretical and computational mathematics, computational biology, mathematical finance, machine learning and more. It is also possible to build your own specialisation, choosing courses after your own interests. For example, you could combine mathematical biology with big data, to create a coherent, individually tailored pathway.

In the second year, you will complete a project course working on real modelling problems together with an industrial partner. This also covers innovation, intellectual property, ethics and commercialisation, and includes close contact with the companies involved. Chalmers has an extensive network of connections with relevant organisations in the region and beyond, such as the Volvo Group, SKF and Ericsson. Thesis projects are also frequently carried out with industry partners, and often students will publish their work in peer-reviewed journals.

One of the key strengths of the programme is its size. It is delivered by the Department of Mathematical Sciences, a joint organisation between Chalmers and the University of Gothenburg, making it the largest mathematics department in all of Sweden. That scale gives you access to an unusually wide range of courses, research environments, and a community of mathematicians and researchers working across a very broad set of fields.

Job opportunities

Advanced mathematical expertise is essential in a world driven by technology, data, and increasingly complex systems. This programme provides a strong foundation in mathematics, statistics, and computational science, preparing graduates to analyse, model, and solve challenging problems in industry, research, and society.

Depending on their specialisation, graduates may work with computational mathematics and scientific computing, mathematical modelling and simulation in engineering, statistical analysis in medicine and public health, quantitative finance, bioinformatics, optimisation and logistics, or data-driven decision making.

Career opportunities exist in consulting, technology-intensive industries, the financial sector, pharmaceutical and biotech companies, healthcare analytics, government agencies, and research organisations. The programme also provides excellent preparation for doctoral studies in mathematics, applied mathematics, statistics, and related disciplines.

Research

Mathematical research at Chalmers is anchored across three main divisions. These are algebra and geometry, applied mathematics and statistics, and analysis and probability theory. Together, these cover the full breadth of the field, spanning computational mathematics, data science, and mathematical biology to name just a few areas.

There are several research centres that are also particularly relevant, including the Chalmers Center for Computational Science and Engineering. This includes infrastructure including CPU and GPU clusters for research into AI and machine learning. The Fraunhofer-Chalmers Research Center for Industrial Mathematics, meanwhile, works with applied mathematical solutions to real engineering and industrial problems in areas like paper and packaging, electronics and life sciences.

You will encounter this research directly through advanced courses, project work, and in your thesis, often working alongside teaching staff on real problems at the frontier of the field.

Requirements

Bachelor's degree in: Science, Engineering, Technology

Prerequisites: Mathematics (at least 37.5 cr. including Linear Algebra, Multivariable Analysis, Mathematical Statistics), Programming (e.g. Python/Matlab/R)

English language requirements: Prove your English proficiency

How to apply

From application to admission

This guide explains how to apply for a Master's programme and which documents you need to submit to complete your application.

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Contact information

Contacts for master's programmes

Here you will find contact information for our master’s programmes starting in the autumn of 2027. Each programme has a Director of Master's programme a Director of Studies and a Student Guidance Counsellor.Below, you will find more information about who to contact. Do you have any questions? Don't hesitate to get in touch.

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