Complex adaptive systems master's programme at Chalmers
To understand the dynamics of increasingly complex phenomena where standard simulation methods are inadequate, stochastic algorithms, game theory, adaptive programming, self-similarity, chaos theory and statistical methods are used to describe and increase our understanding of complex systems in nature and society, in the end trying to predict the unpredictable. Examples are gene-regulation networks, the motion of dust particles in turbulent air or the dynamics of financial markets.
One example is fluctuations in share and option prices determining the stability of our economy. Other examples are the dynamics of dust particles in the exhaust of diesel engines, the dynamics of biological or artificial populations, earthquake prediction, and last but not least adaptive learning: the problem of teaching a robot how to respond to unexpected changes in its environment.
Truly interdisciplinary and encompassing several theoretical frameworks, this programme provides you with a broad and thorough introduction to the theory of complex systems and their applications to the world around us. You will gain the knowledge and the tools needed to model and simulate complex systems and learn how to use and build algorithms for analysis, optimization and machine learning.
The master's programme is based on a physics perspective with a focus on general principles, but it also provides courses in information theory, computer science and optimisation algorithms, ecology and genetics as well as adaptive systems and robotics. Besides traditional lectures on simulation and the theory of complex systems, the programme is largely based on numerical calculations and simulation projects. Depending on your course selection, you will also be able to do practical work in our robotics lab.
What attracted me the most was the robotics track. The coolest thing is that you can tailor your experience to your own interests
The subjects of physics, simulation, modelling, robotics and autonomous systems are fundamental areas in the Complex adaptive systems master's programme. The courses handle topics such as programming, agent-based modelling, network theory, turbulence, genetics, game theory, biophysics, morphogenesis, synchronization, chaotic dynamics, fractals and dynamical stochastic process.
Computer modelling and programming skills, together with expertise in a range of modern algorithms, such as deep machine learning and stochastic optimization, acquired in the programme, open a wide range of possibilities on the job market. Typical employment is often related to data science or advanced engineering topics. For example, in the field of intelligent control systems, such as the development of autonomous driving.
Previous graduates from this programme often find their jobs at larger technology-intensive companies such as Volvo, Volvo Cars, Ericsson, Saab, AstraZeneca, Scania, etc., or smaller start-ups. Some of our previous students have also chosen to continue towards a PhD in a wide spectrum of academic fields ranging from computer science to physics and biotechnology.
The teachers of the master's programme are active researchers in areas closely related to the programme, such as adaptive systems and robotics, genetics and turbulence, machine learning applications in soft matter physics and quantum physics, information theory and game theory.
In addition, there is a wide range of related research activities at Chalmers and the University of Gothenburg, in areas such as deep machine learning, natural language processing, autonomous systems and automation and so on that provide opportunities for elective courses and master's thesis project work.
How to apply - From application to admission
This is a step-by-step guide on how to apply for a Master's programme at Chalmers University of Technology.