Level of education: Aspirantura programme

Type of instruction : Full-time

Duration: 4 years

Language of instruction: Russian

Main academic courses

  • Selected Chapters of Functional Analysis
  • Differential Equations. Supplementary Chapters
  • Homotopic and Algebraic Topology
  • Riemannian, Differential and Metric Geometry
  • Group Theory
  • Galois Theory
  • Approximate Methods of Solving Mathematical Physics Problems. Part 1
  • Modern Methods of Probability Theory and Mathematical Statistics. Part 1
  • Methods and Problems of Statistical Modelling. Part 1
  • Parallel Algorithms and Programming. Part 1
  • Rings and Modules
  • Dynamical Systems. Part 1
  • Limit Theorems of Probability Theory
  • Asymptotic Methods of Probability Theory
  • Homological Algebra
  • Supplementary Chapters of Applied Statistics. Part 1
  • Problems of Mathematical Modelling. Part 1
  • Supplementary Chapters of Complex Analysis
  • Partial Differential Equations and Related Problems. Part 2
  • Theory of Motion Stability
  • Modern Methods of Probability Theory and Mathematical Statistics. Part 2
  • Algebraic Geometry
  • Algebraic Topology
  • Approximate Methods of Solving Mathematical Physics Problems. Part 2
  • Mathematical Cybernetics
  • Qualitative Theory of Dynamical Systems. Part 2
  • Decision Making Problems
  • Methods and Problems of Statistical Modelling. Part 2
  • Parallel Algorithms and Programming. Part 2
  • Stochastic Programming. Part 2
  • Real, Complex and Functional Analysis
  • Geometry and Topology
  • Differential Equations, Dynamical Systems and Optimal Control
  • Mathematical Logic, Algebra and Number Theory
  • Probability Theory and Mathematical Statistics
  • Computational Mathematics
  • Discrete Mathematics and Mathematical Cybernetics
  • Mathematical Modelling, Numerical Methods and Programme Complexes
  • Issues of Modern Calculus of Variations. Part 2
  • Issues of Modern Spectral Theory of Operators. Part 2
  • Dynamical Systems. Part 2
  • Issues of Modern Theory of Random Processes
  • Asymptotic Methods of Mathematical Statistics
  • Algebraic K-Theory
  • Number Theory
  • Supplementary Chapters of Applied Statistics. Part 2
  • Problems of Mathematical Modelling. Part 2

Resource opportunities for research

  • 6.9 million printed books and digital subscription in the M. Gorky Scientific Library of St Petersburg University
  • The Resource Centres of St Petersburg University

Our advantages

  • The programme is designed to train highly qualified experts in the field of mathematics. Its successful mastering: ensures the graduate's professional competencies in the chosen field; makes it possible for them to work successfully in their chosen field of activity; and contributes to a successful academic career and to their being highly in demand in the labour market.
  • While preparing for research activities, doctoral students acquire the skills of independent research that are developed from: the ability to study the literature on the problem including literature in foreign languages; the generation of a mathematical model of the problem; the development of analytical and computer methods for its solution; and a discussion of the results obtained. Doctoral students are taught to: report the results obtained first at seminars among their colleagues, and then at Russian and international scientific conferences, including those in English; and to write articles in Russian and English. While preparing for teaching at higher education institutions, doctoral students are taught to: deliver lectures; conduct practical and laboratory classes; supervise seminars; and communicate properly with students.