KTH Royal Institute of Technology M.S Computer Simulations for Science and Engineering 2025 intake: fees, deadlines, entry requirements, etc.

Year

Course Type

Courses / Specializations

Year 1

Compulsory Courses

- Theory and Methodology of Science

- Sustainable Development and Research Methodology in Mathematics

- Applied Numerical Methods

- Probability Theory

- Finite Element Method

- Matrix Computations

- Numerical Solution of Differential Equations

- Parallel Computations

- Scientific Computing

- Numerical Linear Algebra

- Numerical Mathematics II for Engineering

- Scientific Writing for Mathematics

- Ethics for Applied Mathematics

- Advanced Modeling

- Applied Finite Elements

- Data Assimilation

Elective Courses

- Applied Nonlinear Optimization

- Numerical Methods for Stochastic Differential Equations and Machine Learning

- Topological Data Analysis

- Visualization

- Numerical Algorithms for Data-Intensive Science

- Project Numerical Analysis

- Differential Algebraic Equations

- Control Theory

- Model Reduction

- Mathematical Visualization

- Nonlinear Optimization

- Variational Methods and Optimal Control

- Advanced Topics of Numerical Linear Algebra

- Mathematical Seminar

- Machine Learning I & II

- Non-linear Differential Equations

- Advanced Systems Theory

- Continuous Optimization

- Systems and Control

- Control of Discrete-Time Stochastic Systems

- Special Topics in Computational Science and Engineering

- Linear Algebra and Optimization for Machine Learning

- Scientific Programming for Engineers

- Computational Fluid Dynamics

- Introduction to High-Performance Computing

- Advanced Numerical Methods

- Perturbation and Variational Methods for PDE

- Object-Oriented Programming with C++

Year 2

Specializations

- Biocomputing

- Bioinformatics

- Machine Learning

- Computational Fluid Dynamics

- Numerical Linear Algebra

- Computational Physics

- Numerical Analysis

- Optimal Control

- Control Theory

- High-Performance Computing

- Data Assimilation

Elective Courses

- Advanced Individual Course in Scientific Computing

- Project Course in Scientific Computing

- Program Construction in C++

- Advanced Machine Learning

- Modern Methods of Statistical Learning

- Mathematical Modeling of Biological Systems

- Biomedicine for Engineers

- Bioinformatics and Biostatistics

- Molecular Modeling

- Systems Engineering

- Applied Systems Engineering

- Portfolio Theory and Risk Management

- Risk Management

- Computational Aspects of Stochastic Differential Equations

- Mathematical Data Science

- Parallel Computing

- Computational Finance