15 Apr, 2024Application Deadline
Programme overview
Main Subject
Engineering - Manufacturing and Production
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The ever-accelerating technological progress of today's society requires engineers and scientists that are perfectly equipped with thorough knowledge of natural and materials sciences and who are highly skilled in programming and simulation techniques as well as in data handling and data analysis.
These "Computational Materials Scientists" will become key players in industrial R&D efforts; they will shape scientific and engineering research focusing on the design, processing and application of novel high-tech materials with superior mechanical, thermodynamic, and electronic properties.
At TU Bergakademie Freiberg, we bring together renowned researchers and enthusiastic lecturers from different scientific communities to offer our graduate students the education required for an outstanding career in computational materials science (CMS).
Theoretical concepts introduced during CMS lectures will be illustrated by cutting-edge research applications. An intense introduction seminar will bring you up to speed with scientific programming and modern computing environments. During research seminars, you will have the possibility to interact with leading scientists and experienced engineers from industrial partners. During accompanying hands-on tutorials, the application of all relevant state-of-the-art simulation methods will be learned – which is only one of the truly outstanding aspects of this course. Elective classes will introduce you to specialised topics of computational engineering/mechanics – or even to advanced subjects of data mining and machine learning in data-driven materials science.
Among others, you will learn the theoretical background and hands-on application of the following numerical/simulation methods:
- linear/non-linear finite element methods (FEM)
- molecular statics and molecular dynamics (MS/MD)
- machine learning (ML), deep learning (DL), data analysis
- phase-field method (PFM)
- statistical analysis methods
- Monte-Carlo methods
- cellular automata
- digital image analysis/correlation
CMS students are chosen among the top 5% of their undergraduate classes, ensuring an intense study environment of excellence. Small classes foster interaction and discussions, allowing you to develop your ideas. Furthermore, the study environment shines with an exceptional ratio of teaching staff to the total number of enrolled students.
Programme overview
Main Subject
Engineering - Manufacturing and Production
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The ever-accelerating technological progress of today's society requires engineers and scientists that are perfectly equipped with thorough knowledge of natural and materials sciences and who are highly skilled in programming and simulation techniques as well as in data handling and data analysis.
These "Computational Materials Scientists" will become key players in industrial R&D efforts; they will shape scientific and engineering research focusing on the design, processing and application of novel high-tech materials with superior mechanical, thermodynamic, and electronic properties.
At TU Bergakademie Freiberg, we bring together renowned researchers and enthusiastic lecturers from different scientific communities to offer our graduate students the education required for an outstanding career in computational materials science (CMS).
Theoretical concepts introduced during CMS lectures will be illustrated by cutting-edge research applications. An intense introduction seminar will bring you up to speed with scientific programming and modern computing environments. During research seminars, you will have the possibility to interact with leading scientists and experienced engineers from industrial partners. During accompanying hands-on tutorials, the application of all relevant state-of-the-art simulation methods will be learned – which is only one of the truly outstanding aspects of this course. Elective classes will introduce you to specialised topics of computational engineering/mechanics – or even to advanced subjects of data mining and machine learning in data-driven materials science.
Among others, you will learn the theoretical background and hands-on application of the following numerical/simulation methods:
- linear/non-linear finite element methods (FEM)
- molecular statics and molecular dynamics (MS/MD)
- machine learning (ML), deep learning (DL), data analysis
- phase-field method (PFM)
- statistical analysis methods
- Monte-Carlo methods
- cellular automata
- digital image analysis/correlation
CMS students are chosen among the top 5% of their undergraduate classes, ensuring an intense study environment of excellence. Small classes foster interaction and discussions, allowing you to develop your ideas. Furthermore, the study environment shines with an exceptional ratio of teaching staff to the total number of enrolled students.
Admission Requirements
Scholarships
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