Applied Mathematical Stochastic Methods

Course characteristics

The master´s degree course in Applied Mathematical Stochastic Methods is multi-disciplinary in character. It is oriented to advanced sections of applied mathematical statistics. The course orients graduates in solving problems in natural sciences and engineering.

The courses are devoted to in-depth study of the areas mentioned above and students should acquire a significant insight into state-of-the-art of the field. The curriculum includes an individual student project on an assigned topic done independently. The project helps the student to understand issues in the field and often offers original results publishable in scientific journals.

Specialised courses of the degree course provide students with a knowledge of mathematical statistics methods, probability theory, and stochastic processes in situations encountered in materials or transport engineering.

Graduate's profile

Knowledge: The graduate acquires a broad knowledge of advanced mathematics and informatics furthered by understanding the stochastic processes.

Skills: The graduates have the capability to use methods and techniques of selected areas of applied mathematics and physics in solving real-life engineering, research, and scientific problems. In addition to the specialised skills gained during the course, graduates also possess other skills, e.g. adaptability, a quick grasp of unfamiliar interdisciplinary problems, and problems analysis and its corresponding computer processing, analysis, and synthesis. Good writing skills are also part of the graduate´s profile. A sense of responsibility in performing tasks and in decision making is a matter of course.

Competency: Positions for the graduates are open mainly in industry, research, and the private sector, and their capabilities to use highly analytical methods of work and systematic approach to solving problems with modern information technologies are highly appreciated. Such positions are usually open in the institutes of the Czech Academy of Sciences and in research and development centres of large enterprises or other research institutes.

State final examination

• Applications of mathematical statistics and information theory - compulsory subject
• Image processing and pattern recognition - compulsory subject
• Generalized linear models - elective subject
• Systems with social interactions - elective subject
• Signals processing - elective subject