Mathematical Engineering

Research field abbreviation: MI
Field code: 3901V021
Course duration: 4 years

Field specialisations

• Mathematical Modelling
• Mathematical Physics
• Software Engineering

Research field characteristics

The study field of Mathematical Engineering offered by the Faculty of Nuclear Sciences and Physical Engineering is within the competence of the Department of Mathematics in cooperation with the Department of Physics and the Department of Software Engineering. Mathematical Engineering is interdisciplinary in nature, because it combines theoretical mathematical knowledge in many fields of natural sciences and engineering and applies it to mathematical modelling of processes in nature, engineering, and environmental protection; in the modern disciplines of mathematical physics; in theoretical computer science; and in discrete mathematics and software engineering, especially as applied to natural sciences.

Many academics from the Department of Mathematics share in the task of educating students on the advanced academic courses, along with academics from many significant research institutes of the Czech Academy of Sciences (CAS) (the Institute of Computer Science, Institute of Information Theory and Automation, Institute of Physics, Nuclear Physics Institute, and Institute of Thermomechanics). The department also hosts internationally acclaimed teams, often involved in solving problems cooperatively.

Graduate's profile

The doctoral course in Mathematical Engineering offers an even more profound and advanced insight into the level of disciplines acquired in the master course.

Graduates are profiled in one of the elected areas of modern mathematics (e.g. advanced functional analysis, algebraic structures, stochastic processes, aperiodic structures, non-linear partial differential equations) as well as in a broad field of applications (e.g. quantum mechanics, particle physics, materials science, advanced methods of computer science, and environmental protection). The doctoral thesis is then a proof of the student´s mastery of both selected parts of modern mathematics and their creative interdisciplinary applications. A significant asset of the course is that all doctoral students join research teams either directly at their department or at cooperating institutions, in particular institutes of the Czech Academy of Sciences (CAS) (see above) and they often participate in large-scale projects of multinational teams abroad. The course can also be organised under dual supervision as a joint-degree course together with a distinguished foreign university (France, Germany). Doctoral students are encouraged to present their results at international conferences and publish them in prestigious scientific journals.

PhD course graduates have the educational attainments to embark without difficulty on a career both in fundamental and applied research, gain a postdoctoral fellowship from a foreign or domestic university, start their academic career at a university or a research institute, or even enter highly qualified positions in finance or software and computer companies.

Specialisation

The doctoral programme in Mathematical Engineering is offered by the Department of Mathematics and includes the following specialisations: Mathematical Modelling and Software Engineering, and, in cooperation with the Department of Physics, Mathematical Physics.

• Mathematical Modelling is theoretically focused on the development and analysis of deterministic and stochastic models of numerous fields of research in physics, engineering, medicine and economy.
• Mathematical Physics focuses on mathematical problems of Quantum Theory. In particularly abstract mathematical models using computers for numerical and symbolic computations and simulations of physical processes are researched. Many dissertation topics proceed from research projects supported by grant agencies.
• Software Engineering focuses on mathematical problems related to information technology and often to the development of extensive computer programs designed to solve specific research and commercial projects such as large international experimental projects in particle physics (CERN, Brookhaven National Laboratory) as well as to processing data from the monitoring of patients with a disease. Solutions to research and commercial issues often result from the creation and implementation of algorithms.