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Graduate courses

Departments' graduate courses for PhD-students.

  Study programme, year:  1 2

Study programme syllabus for
Associated to: TKTFY
The Study programme syllabus is adopted 2019-02-20 by Dean of Education and is valid for students starting the programme the academic year 2019/2020

Entry requirements:

General entry requirements:

Basic eligibility for advanced level


Specific entry requirements:


English proficiency:

An applicant to a programme or course with English as language of instruction must prove a sufficient level of English language proficiency. The requirement is the Swedish upper secondary school English course 6 or B, or equivalent. For information on other ways of fulfilling the English language requirement please visit Chalmers web site.


Undergraduate profile:

Major in Engineering Physics, Physics, Electrical Engineering, Mechanical Engineering, Automation and Mechatronics Engineering, Computer Science, Computer Engineering, Mathematics, Chemical Engineering, Chemistry, Bioengineering or the equivalent.



Mathematics (at least 30 cr.) (including Linear algebra and Mathematical analysis) and Programming.

General organization:


The purpose of the master program is to provide the student with knowledge and tools for modeling and simulating complex systems, and to understand and be able to use related algorithms for optimization and machine learning. The specificity of the program is to study both fundamental aspects of complex systems in nature and society and to link this with understanding of and skills to use modern algorithms. Major focus is on the use of computers and relevant software for simulation and problem solving. At the same time, the program assumes good mathematical knowledge which is used and built on to give a theoretical depth in the understanding of the methods.

The program provides suitable background both for postgraduate education in areas such as physics / statistical physics, system biology, or computer science, and work as an engineer in a wide range of areas depending on bachelor program and specialization in the master program. For example, machine learning and artificial intelligence are areas of rapid advancement where students from CAS are particularly well-suited to work.


Learning outcome:

The MSc programme in Complex Adaptive intends to enable its students to achieve the following learning outcomes, fulfilling the requirements of the 'Swedish degree ordinance for the civilingenjör degree'.

1. Knowledge and understanding.
Upon completion of the programme, students should
[1.1] have obtained general knowledge of the significance of, the problems posed by, and the methods employed in understanding complex systems observed in the Natural and Engineering Sciences.
[1.2] have obtained practical experience in the mathematical analysis and computer modeling of complex systems
[1.3] have obtained significantly deepened knowledge of the presently most pressing problems, the currently employed techniques, and the recent advances in understanding complex systems in one of the following areas: adaptive systems, information & evolution, or stochastic dynamics of complex systems.

2. Skills and abilities.
 Upon completion of the programme, students should
[2.1] be able to construct mathematical models of complex systems, and make quantitative predictions based upon them, employing mathematical reasoning and  simulations
[2.2] have acquired the modeling skills to work successfully under supervision in one of the above areas, or to apply their problem-solving skills in a suitable industry project in collaboration with their academic teachers, and last but not least to use their skills effectively in new or initially unfamiliar, interdisciplinary environments.
[2.3] be able to analyse and critically evaluate technical solutions, mathematical models, and scientific approaches, and to critically and systematically integrate knowledge
[2.4] be able to plan their work  withinin given time and methodological constraints
[2.5] be able to communicate their results and conclusions (orally and in writing in national as well as in international contexts),  and to describe the hypotheses and assumptions these rest on to specialist and to non-specialist audiences.
[2.6] be able to continue to study or work independently, autonomously, and self-directed if necessary, but they should also be able to work successfully in an interdisciplinary  team.

3. Formulation of judgments and attitudes.
Upon completion of the programme, students should be able to
[3.1]  demonstrate the ability to formulate judgments considering relevant scientific, societal and ethical aspects, and demonstrate an awareness of ethical aspects on research and development work,
[3.2] demonstrate insight into the possibilities and limitations of technology, its role in society and the responsibility of humans for its use, including social, economic as well as environmental and occupational health aspects, and
[3.3] demonstrate ability to identify their need for more knowledge, and to continuously develop their competence. 


Extent: 120.0 c


Courses valid the academic year 2019/2020:

See study programme


Accredited to the following programmes the accademic year 2019/2020:

Degree of Master of Science in Engineering

 Degree requirements:
  Degree of master of science (120 credits):
Passed courses comprising 120 credits
Passed advanced level courses (including degree project) comprising at least 90 credits
Degree project 30 credits
Advanced level courses passed at Chalmers comprising at least 45 credits
Courses (including degree project) within a major main subject 60 credits
Fulfilled course requirements according to the study programme
The prior award of a Bachelors degree, Bachelors degree in fine arts, professional or vocational qualification of at least 180 credits or a corresponding qualification from abroad.

See also the Local Qualifications Framework - first and second cycle qualifications

Title of degree:

Master of Science (120 credits). The name of the Master's programme and the major subject Engineering Physics are stated in the degree certificate. Specializations and tracks are not stated.


Major subject:

Engineering Physics

Other information:

Programme idea.
The basic method of learning is problem solving in the form of assignments and smaller projects. In all courses, the emphasis is on problems that require solutions to be implemented with mathematical software (typically Matlab). One of the courses in study period 1 (Stochastic optimization) also emphasizes the importance of writing structured program code and examins this. In several courses, one works in groups of two (sometimes more) students, which is also an important aspect of the program.

As a supplement to the project-oriented structure, most courses are also given a written exam. These too are problem-oriented, but also address more conceptual aspects and test the basic understanding. Written exams are especially important to ensure that the examination is individual.

One of the compulsory courses is a seminar course that spans the entire first year. This is intended to function partly as an introduction, but also to give training in presentation techniques by systematically giving and receiving feedback on presentations. This course also includes an ethical element, addressing for example ethical challenges in developing AI.

Link to industry
Students of the programme frequently work on their MSc project at companies in the Gothenburg region, in other regions in Sweden, as well as abroad.

Page manager Published: Thu 04 Feb 2021.