Study programmes for academic year 2018/2019
|Faculty||Faculty of Science|
|Study, form, type||single-major, full-time, doctoral|
|Language of instruction||English|
|Length of study (years)||4|
|Estimation of admissions next year|
|Study guaranteed by||Fišerová Eva, doc. RNDr. Ph.D.|
The study provides a deeper knowledge of fundamental theoretical disciplines used in various branches of applied mathematics (probability theory and mathematical statistics, fuzzy sets theory, methods of decision making and evaluation, numerical and optimisation methods, partial differential equations). The students acquire a deeper knowledge of the selected topics of their theses, learn how to process them independently in terms of theory, verify the models or solve the problems theoretically in computer implementation. Some of the Ph.D. theses contain beside the theoretical part also the solution of the chosen difficult problem from real life. The dissertation topics are chosen usually from the following areas: (a) regression models with complicated structures, statistical modelling and statistical analysis of compositional data with the applications in medicine, chemometrics, natural sciences and others, (b) utilizing the tools of fuzzy sets theory for modelling uncertain data and expert knowledge in economy, psychology, medicine and other fields, development of fuzzy methods of decision making and evaluation, (c) continuum mechanics, shape optimisation, solutions to problems of fluid mechanics and non-linear elliptic problems, their characteristics and numerical solutions of the arising sets of equations. All of these topics are currently objects of an intensive research in the department.
Requirements for admission
Master degree in mathematics.
Successful entrance interview.
Programme teaching goals
The study program aims at molding knowledgeable experts in various fields of applied mathematics (probability theory and mathematical statistics, fuzzy sets theory, methods of evaluation and decision making, numerical and optimization methods, partial differential equations) who passes both firm theoretical knowledge and the ability of applying their knowledge to real-world problems. With selected topics, emphasis is therefore placed on software implementation of new theoretical results, with a view of extensive computer simulations as well as analysing data originating in different fields.
The graduate has mastered a vast body of knowledge in a specific field of applied mathematics (probability theory and mathematical statistics, fuzzy sets theory, methods of evaluation and decision making, numerical and optimization methods, partial differential equations). Moreover, he is able to invent new mathematical models and implement them in a particular software environment. He is also well equipped to work with real-world data, appropriately applying mathematical procedures.
Universities, enterprising, state authorities.
Possible job positions
Data analyst, system analyst, researcher.