Charles University

Overview

The Master's program in Computational Mathematics at Charles University is designed to equip students with the skills necessary to develop, analyze, and implement numerical methods for solving complex mathematical models on computers. This program emphasizes the design of algorithms, the assessment of their accuracy and stability, and their application to real-world challenges.

• Degree level: Master’s (MSc)
• Focus: Numerical mathematics, computational methods, and mathematical modeling
• Delivery format: On-campus
• Language of instruction: English
• Typical duration: 24 months

What you'll study

The curriculum is structured to provide a comprehensive understanding of computational mathematics, combining foundational courses with advanced topics. Students will engage in a variety of subjects, allowing them to progress from theoretical concepts to practical applications and validation of computational results.

• Finite Element Method
• Matrix Iterative Methods
• Inverse Problems and Regularization
• Parallel Matrix Computations
• Sparse Matrices in Direct Methods
• Numerical Optimization Methods
• Nonlinear Differential Equations

Capstone / thesis: As part of the program, students are typically required to complete a master’s thesis or equivalent final project, which showcases their understanding and application of the concepts learned throughout the course.

Entry requirements

To apply for the MSc in Computational Mathematics, candidates should possess a relevant Bachelor’s degree or be in the final stages of completing one. A strong academic foundation in mathematics and numerical or computational methods is essential. The program is inclusive of students from diverse mathematical backgrounds, including those who may need to address any knowledge gaps.

Career prospects

Graduates of the Computational Mathematics program are well-prepared for various career paths in fields such as data analysis, software development, engineering, and research. The skills acquired during the course enable them to tackle complex problems in industry and academia, making them valuable assets in the rapidly evolving technological landscape.