Mathematical Modelling, Programming and Artificial Intelligence

• The degree programme is aimed at training experts who are capable of: independently setting and solving theoretical and practical tasks in this and related subject areas; independently conducting research in areas that use methods of applied mathematics and computer technology; developing and using mathematical models of processes and objects; developing and applying cutting-edge mathematical methods and software to solve problems of science, technology, economy and management; and applying effective mathematical approaches in the field of artificial intelligence systems and modelling of complex systems.
• Students will learn how to: formalise the original problem; construct mathematical models and verify their adequacy; develop known and create new methods of solving mathematical physics problems; apply methods of paralleling calculations to solve practical problems; create a computer implementation of the resulting solutions; use effectively statistical and mathematical packages; create effective computer realisations of statistical methods for solving practical problems; and develop known and create new statistical methods of data processing.
• Graduates of the programme will be capable of carrying out research, design, engineering and manufacturing, organisational and managerial, and teaching work related to: the use of mathematics, programming, information and communication technology and automated control systems; mathematical and statistical modelling; and the development of software for science and industry.

Professions

• Analyst
• Statistician
• Analyst-programmer
• Software engineer
• Teacher of vocational education, and lifelong professional education and training
• Information systems specialist
• Research associate

• The European Embedded Control Institute (EECI) (France)
• The Norwegian University of Science and Technology (Trondheim, Norway)
• The Eindhoven University of Technology (the Netherlands)
• The Institute for Theoretical Physics of the Technische Universität Berlin (Germany)
• The University of Jyväskylä (Finland)
• Lappeenranta-Lahti University of Technology (Finland)

• Algebraic Problem of Eigenvalues and Solution of Mathematical Physics Problems
• High-Performance Computing and Paralleling
• Parallel and Distributed Computing
• Computer Convex Programming Methods
• Fundamentals of Multi-Body System Dynamics
• Graph Theory
• Artificial Intelligence
• Mathematical Modelling of Cybernetic and Robotic Systems
• Introduction to Cybernetic Systems Theory
• Frequency Methods of Nonlinear System Analysis
• Computer Vision Algorithms
• Autonomous Robot Navigation and Motion Control
• Machine Learning
• Programming the Robots
• Artificial Neural Networks and Big Data Processing

• Theory and applications of randomised quasi-Monte Carlo methods (research supervisor: Professor Sergei Ermakov)
• Deterministic and chaotic dynamics of synchronisation and control systems (research supervisor: Professor Nikolay Kuznetsov)
• Analytical and numerical methods and artificial intelligence in the analysis of multi-stability and hidden oscillations of dynamic systems (research supervisor: Professor Nikolay Kuznetsov)
• Control of mechatronic and robotic systems under limited resources (research supervisor: Professor Alexey Matveev)
• Oscillations and stabilisation of systems with pulse modulation (research supervisor: Professor Alexander Churilov)
• Development of mathematical methods for optimal planning and analysis of regression models (research supervisor: Professor Viatcheslav Melas)
• Development of mathematical methods for the analysis and forecasting of onedimensional and multidimensional time series within the framework of the singular spectrum analysis (research supervisor: Associate Professor Nina Golyandina)