Complex Adaptive Systems, MSc

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Overview

  • Educational areaEngineering Physics and Mathematics
  • DegreeMaster of Science, MSc
  • LanguageEnglish
  • Duration2 years
  • Rate of studyFull-time, 100 %
  • Instructional timeDaytime

Important dates

  • Application opens
  • Application closes

Summary

How can we understand and predict the complex behaviours of systems made up of thousands of interacting parts? Flocks of birds changing direction, financial markets reacting to breaking news, or machine learning systems that can speak and move. Learn the mathematical and computational principles that can help you to analyse, model, and work with these kinds of systems.

Programme description

Complex adaptive systems are hugely varied, and cover many academic fields. Widely used methods like genetic algorithms and artificial neural networks, for example, have roots in biology and physics.

This programme will develop your understanding of these methods alongside the practical computational skills to apply them. You will work with mathematical modelling, computer simulation, and programming intensively throughout. Many of the courses involve project work in teams with students from other backgrounds, reflecting the varied nature of the field. These projects often involve real problems contributed by industry or academic partners such as pharmaceutical firm AstraZeneca, or Gothenburg’s Sahlgrenska University Hospital.

You will begin by building a strong foundation, with courses covering areas like artificial neural networks, stochastic optimisation algorithms, dynamical systems, and simulation of complex systems.

This early focus will help you understand the essential broader concepts of the field, before you go deeper through elective courses and specialisations. These cover advanced areas of the field, including quantum computing, machine learning and embodied systems.

You will graduate with a broad understanding of complex systems of many varieties, combined with specialist knowledge in areas such as mathematics, machine learning, quantum systems or biological systems.

Job opportunities

The combination of natural science foundations, machine learning expertise, and computational modelling skills means that you will graduate with a skillset that is genuinely unique in the job market, and increasingly sought after., You will be well positioned for roles in high-tech industries, including data-intensive sectors like finance, pharmaceuticals, and energy, as well as in research-oriented organisations working with AI, robotics, autonomous systems, or quantum computing.

Chalmers’ education in these areas is well-established and highly respected in Gothenburg and beyond, as a benchmark for strong analytical and computational ability. Many graduates move directly into industry roles at companies working in these fields. Alternatively, you will be ideally placed to continue on to doctoral studies in many fields, from physics and computer science to mechanical engineering and automation, either at Chalmers or elsewhere.

Research

Chalmers has international research excellence in AI, machine learning, quantum computing, algorithms, statistical physics and many more relevant disciplines. All of these research areas feed directly into the courses and specialisations.Many courses are taught by researchers working at the frontier of their subject.

Several courses are shared with other master's programmes, broadening the research connections available to students and reflecting the varied nature of the field. Master's thesis projects can spread across all these research environments, or in collaboration with external industry or academic partners.

Requirements

Bachelor’s degree in: Physics, Mathematics, Chemical Engineering, Computer engineering, Mechatronics engineering, or the equivalent
Prerequisites: Mathematics (at least 24 cr. including Linear algebra and Mathematical analysis), Programming in a General-Purpose Language (at least 6 cr. e.g. Python, Java, C++, or similar)

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.