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Admission Educational Programmes Graduate

Mathematical Modelling, Programming and Artificial Intelligence

01.04.02 In russian

Level of education Master

Type of instruction Full-time

Duration 2 years

Programme description
  • The programme is designed for applicants with bachelor’s degrees and for students with different levels of training in mathematics.
  • It is based on individual educational trajectories, aimed to meet employers' requirements for employee qualifications to the maximum extent possible. This enables graduates of the programme to: acquire the knowledge, skills and abilities they need; and start work with a minimum adaptation period.
Our advantages
  • 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.
Career opportunities
Professions
  • Analyst
  • Statistician
  • Analyst-programmer
  • Software engineer
  • Teacher of vocational education, and lifelong professional education and training
  • Information systems specialist
  • Research associate
International relations
  • 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)
Main courses
  • 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
Main areas of research
  • 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)

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