The doctoral program in Informatics is designed according to the planned research topics of doctoral students, as well as qualification training courses in this field of science. The purpose of the doctoral program is to train scientists, who would be capable of independently carrying out research and experimental development and solving scientific problems of Informatics.

Research topics of doctoral students in Informatics:

  • Computer Modeling of Physical, Chemical, Biological and Social Systems
  • Network Models and Algorithms
  • Large-scale Data Research
  • Visualization of Multidimensional Data
  • Optimization Algorithms and Their Applications
  • Artificial Intelligence and Machine Learning
  • Algorithm Complexity Theory: The problem of Lower Estimates
  • Investigation of Operations
  • Artificial Neural Networks, Deep Learning
  • Formal Modeling, Verification and Numerical Evaluation of Computer Systems
  • Information Systems and Decision-making Methods

The study program consists of two blocks for subjects: compulsory block and elective block. The compulsory block consists of the subject for all the doctoral students and it reflects the main research topics for doctoral students, providing them with access to the general qualifications required for research. An elective block offers the subjects from which the rest of the program may be chosen and it is based on the research topics of Informatics. With the approval of the PhD Committee, students can choose the subject in other fields of science.

Compulsory block

  • Research Methods in Informatics and Informatics Engineering
  • Fundamental Methods of Informatics and Informatics Engineering

Elective block

  • Automated Methods of Verification and Validation
  • Visualization of Multidimensional Data
  • Efficient Algorithms
  • Deep Neural Networks
  • Applications of Classical Geometry in Surface Modeling
  • Computer Modeling of Curves and Surfaces
  • Nonlinear Statistical Models in Mass Data Analysis
  • Optimization Methods and Their Application
  • Process Evaluation and Improvement Models
  • Software Systems Semantics and Specification Languages
  • Numerical Intelligence Investing in Securities
  • Numerical Modeling
  • Statistical Modeling and Stochastic Optimization
  • Modern Database Systems
  • Network Models and Algorithms

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