MSc in Complex Adaptive Systems
Gothenburg, Sweden
DURATION
2 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
Request application deadline
EARLIEST START DATE
Request earliest startdate
TUITION FEES
SEK 160,000 / per year *
STUDY FORMAT
On-Campus
* tuition fees for non-EU/EEA students
Introduction
The human brain, economic markets, our immune systems — even the formation of clouds. All examples of complex adaptive systems, formed from multiple interacting components, often non-linear and dynamic, lead to a collective structure and organization across multiple levels.
The behaviour of complex adaptive systems in nature has served as inspiration for all sorts of advances and methodologies in information processing, from artificial neural networks inspired by neurobiology to genetic algorithms and programming based on natural evolutionary processes — even the design of artificial life. Further examples include the fluctuations of stocks and shares, the dynamics of dust particles in engine exhausts, and earthquake prediction. The challenges of adaptive learning — teaching robots to respond to unexpected changes in their environment, for example, is also an extremely important emerging field.
With a truly interdisciplinary approach, encompassing several theoretical frameworks, this Master’s program will provide you with a broad and thorough introduction to the theory of complex adaptive systems and their application to the world around us. You will gain the knowledge and tools necessary to model and simulate complex systems, learning how to use and build algorithms for analysis, optimization, and machine learning.
The program is based on a physics perspective, with a focus on general principles, but we also offer courses in information theory, computer science, optimization algorithms, ecology, and genetics, as well as adaptive systems and robotics. Besides traditional lectures on simulation and the theory of complex systems, the program 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.
The subjects of physics, simulation, modelling, robotics, and autonomous systems form the fundamental areas of the master's program. Elective courses handle a very wide range of topics, including programming, network theory, turbulence, genetics, game theory, biophysics, chaotic dynamics, fractals, and dynamical stochastic processes.
Admissions
Scholarships and Funding
Scholarships are a great source of funding for Master's students who are liable to pay tuition fees. Some of these are administrated by Chalmers and others by external institutions. Additional scholarships may be appended to the list and applicants are therefore encouraged to check this webpage regularly.
Please visit the university website for more information.
Curriculum
Compulsory courses year 1
During the first year, the program starts with six compulsory courses that form a common foundation in Complex adaptive systems. Each course is usually 7.5 credits.
- Artificial neural networks
- Simulation of complex systems
- Stochastic optimization algorithms
- Dynamical systems
- Computational biology 1
Compulsory courses year 2
In the second year, you must complete a master's thesis to graduate. The thesis may be worth 30 credits or 60 credits depending on your choice.
- Master's thesis
Program Tuition Fee
Career Opportunities
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 employments are 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 students 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.