Master in Computational Materials Science
Malmö University
Key Information
Campus location
Malmö, Sweden
Languages
English
Study format
On-Campus
Duration
2 years
Pace
Full time
Tuition fees
SEK 300,000 / per course *
Application deadline
Request info
Earliest start date
02 Sep 2024
* full tuition fee
Introduction
The Computational Materials Science master’s program prepares you for a career at the cutting edge of materials development. This is an area where computer simulations and algorithms play a critical and expanding role. New and improved materials will form the basis for new technologies. Through this program, you can contribute to overcoming the many daunting challenges regarding materials that industry and the greater society face.
This program will provide you with a robust background in computational materials science. It will also give you the tools you need to begin or advance your career, either in industry or in academic research.
A mix of materials science and computation
The program features a mix of content in materials science and computation and includes both foundational courses and those covering advanced applications. The latter includes scientific programming and implementation of various models with Python and Matlab, electronic and atomistic modeling with professional tools like QuantumEspresso and LAMMPS, and component- and micro-scale finite element modeling using professional engineering packages. Other courses provide you with surveys of important concepts and applications in modern materials science, as well as an introduction to the advanced X-ray and neutron techniques used for materials research at the state-of-the-art facilities MAX IV and ESS, located in nearby Lund. The 2-year program concludes with a 30-credit thesis on a topic of interest to the student.
Skills for industry
The development, reliable production, and application of high-performance materials are key to competition for companies operating in many sectors, from energy and transportation to consumer electronics and food packaging. Rapidly expanding computer power and new algorithms mean that companies can increasingly replace relatively slow and expensive experimental materials development with computer simulations. This allows companies to speed up their R&D, reduce its costs, and improve product reliability. Companies need engineers with skills in both computational methods and materials science. Our program develops these skills and teaches you how to connect them to solve real material problems.
Malmö University has close connections with several Swedish companies. Students who are interested in moving directly to industry are encouraged to carry out thesis projects in collaboration with one of these companies or to seek out new opportunities in line with their interests at others. In this way, they will expand their professional networks and gain experience working in the private sector environment while demonstrating and further developing their technical skills.
Admissions
Curriculum
Organisation
The programme allows the student to gain deeper knowledge and skills within computational materials science. The student will also acquire knowledge and skills related to methods applied for research and development within materials science.
Contents
Semester 1, Autumn 2024
- Materials Engineering MT640E, 7.5 credits
- Scientific Programming MA620E, 7.5 credits
- Differential Calculus in Several Dimensions MA621E, 7.5 credits
- Phase Transformations MT641E, 7.5 credits
Semester 2, Spring 2025
- Introduction to Numerical Analysis MA623E, 7.5 credits
- Quantum Mechanics: Introductory course FY242E, 7.5 credits
- Continuum Mechanics MT643E, 7.5 credits
- Synchrotron- and Neutron-Based Experimental Methods and Applications MT644E, 7.5 credits
Semester 3, Autumn 2025
- Density Functional Theory MT645E, 7.5 credits
- Finite Element Method and Constitutive Modelling MT646E, 15 credits
- Classical Molecular Dynamics Modelling MT647E, 7.5 credits
Semester 4, Spring 2026
- Master Thesis in Materials Science (two years) MT648E, 30 credits
Program Outcome
Knowledge and understanding
To receive a master’s degree in Computational Materials Science, the student shall:
- Demonstrate knowledge and understanding of materials science, comprising broad knowledge within the field and substantial specialized knowledge within certain parts of the field, in addition to specialized insight into relevant research and development work; and
- Demonstrate specialized methodology knowledge within materials science.
Skills and abilities
To receive a master’s degree in Computational Materials Science, the student shall:
- Demonstrate the ability to critically and systematically integrate knowledge and to analyze, assess, and handle complex phenomena, issues, and situations, even with limited information
- Demonstrate the ability to identify and formulate issues critically, autonomously, and creatively as well as to plan and, using appropriate methods, undertake advanced tasks within predetermined time frames, thereby contributing to the formation of knowledge as well as developing the ability to evaluate this work
- Demonstrate the ability in both national and international settings to clearly describe and discuss their conclusions and the knowledge and arguments on which these are based, in dialogue with different groups, both orally and in writing; and
- Demonstrate the skills required to take part in research and development work or independent work for another advanced enterprise
Judgment and approach
To receive a master’s degree in Computational Materials Science, the student shall:
- Demonstrate the ability, within materials science, to make judgments about relevant scientific, social, and ethical factors, and demonstrate awareness of ethical issues in research and development work
- Demonstrate an insight into the opportunities and limitations of science, the role these play in society, and individuals’ responsibility for how this is applied; and
- Demonstrate the ability to identify personal needs for further knowledge and to take responsibility for their ongoing learning