Computational Mathematics

The target group of the doctoral program in computational mathematics are mathematicians and computer scientists with an interest in research in the field of numerical analysis and approximation theory, with a desire for an academic career or realization of research teams in the industry. 

The training in the doctoral program is aimed at building scientists with skills for research and teaching at a high level. During their studies, doctoral students acquire solid knowledge in their chosen subfield of computational mathematics - a classic and at the same time modern, rapidly developing branch of applied mathematics.

The main subfields of computational mathematics on which the doctoral program focuses are numerical analysis, approximations of functions and functionalities, extreme problems for polynomials and spline functions, multidimensional approximations, depending on the specific interests and desire of doctoral students for the research part of their doctoral studies. In addition to the listed theoretical areas, doctoral students can gain knowledge and skills for research in other applied areas such as numerical methods, mathematical modeling in biology, physics, mechanics, and others.

During their studies, doctoral students become part of the academic community of the Faculty of Mathematics and Informatics and work in direct contact with researchers in the field of computational mathematics. This is done through their active participation in seminars, national and international schools and conferences, through informal discussions. In this way they are directly informed about the current state of research in their field, receive ideas for new directions in their work and promote their results around the world and in our country. Joining extremely high-level working groups and encouraging teamwork are additional benefits.

Professional area: 
4.5. Mathematics
Degree: 
Educational and Scientific Degree “Doctor”
Programme code: 
MI45M0701D / MI45M0702D / MI45M0703D
Form of education: 
full-time / part-time / self-study