Required motivation and academic background
The formal requirement for the Master’s program Simulation Sciences is a Bachelor’s degree in natural science, mathematics, computer science, or engineering.
Beside this and in order to study Simulation Sciences successfully, the following characteristics and previous knowledge should be there. Please note, that not necessarily all of the below listed knowledge / courses need to be covered; it should be a large fraction though. In any case it is essential to hold the mentioned characteristics (interests and skills).
Characteristics:
• Desire to obtain a deeper interdisciplinary understanding in new scientific areas
• Interest in learning how to transfer scientific problems into models and computer algorithms
• Understanding complex programming issues on different computer architectures as an interesting challenge
• Persistence in technical and scientific problem solving
• High motivation for self-study
• Sufficient proficiency in English
Previous knowledge:
General
• Knowledge of a programming language such as C, C++, Fortran or others
• Basic knowledge of programming techniques
• Basic experience with Linux / Unix operating systems
Mathematics
• Analysis
• Linear algebra
• Statistics
• Numerics
Basic knowledge / courses in several of the following disciplines:
Physics
• Classical mechanics
• Electrostatics
• Magnetism
Chemistry
• General chemistry
Computer science
• Algorithms (e.g. recursions, complexity analysis)
• Software analysis (e.g. object-oriented programming)
Engineering
• Fluid dynamics
• Structural mechanics
• Thermodynamics
Beside this and in order to study Simulation Sciences successfully, the following characteristics and previous knowledge should be there. Please note, that not necessarily all of the below listed knowledge / courses need to be covered; it should be a large fraction though. In any case it is essential to hold the mentioned characteristics (interests and skills).
Characteristics:
• Desire to obtain a deeper interdisciplinary understanding in new scientific areas
• Interest in learning how to transfer scientific problems into models and computer algorithms
• Understanding complex programming issues on different computer architectures as an interesting challenge
• Persistence in technical and scientific problem solving
• High motivation for self-study
• Sufficient proficiency in English
Previous knowledge:
General
• Knowledge of a programming language such as C, C++, Fortran or others
• Basic knowledge of programming techniques
• Basic experience with Linux / Unix operating systems
Mathematics
• Analysis
• Linear algebra
• Statistics
• Numerics
Basic knowledge / courses in several of the following disciplines:
Physics
• Classical mechanics
• Electrostatics
• Magnetism
Chemistry
• General chemistry
Computer science
• Algorithms (e.g. recursions, complexity analysis)
• Software analysis (e.g. object-oriented programming)
Engineering
• Fluid dynamics
• Structural mechanics
• Thermodynamics