Skoltech is an international graduate research-focused university that was founded by the group of world-renowned scientists in 2011. Skoltech's curriculum focuses on technology and innovation, offering Master's programs in 11 technological disciplines. Students receive rigorous theoretical and practical training, design their own research projects, participate in internships and gain entrepreneurial skills in English. The faculty is comprised of current researchers with international accreditation and achievements.

Math of Machine Learning

Master of Science Program 

Modern Machine Learning is at the cutting edge of various disciplines of mathematics and computer science. Math of Machine Learning is one of the most dynamic areas of modern science, encompassing mathematical statistics, machine learning, optimization, and information and complexity theory. From the start of the program, students collaborate in thematic working groups and actively participate in research, learning from Skoltech and Higher School of Economics scientists as well as leading global specialists in statistics, optimization and machine learning.

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 Application dates


Key information

Program starts
September 1
Modes and duration
Full time:
 2 years
Tuition fees
No tuition fee
 for applicants who pass the selection process

Awarded degree
Master of Science in Data Science

Field of Science and Technology
02.04.01 Mathematics and Computer Science

Language of instruction
The program is accredited by the Russian Government, certificate № 2568 from April 14, 2017. License № 2534 from February 7, 2017.

Entry requirements

Skills and Knowledge: Calculus, Differential Equations, Linear algebra, Probability theory and mathematical statistics, Discrete mathematics (including graph theory and basic algorithms), Programming.

Education: Math or IT-related bachelor’s degree or its equivalent in Pure and Applied Mathematics/Computer Science/Statistics or other technical areas.

English language requirement: If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

English language requirements
If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

A successful graduate of this track will:

  • possess active knowledge of modern methods and approaches in statistical learning, including mathematical statistics, stochastic processes, convex optimization
  • be able to apply and further develop such methods for solving complex practically motivated problems of data analysis 

Aim and objectives

The aim of the program is to prepare the technological leaders of the future. The objective of the MSc program is to bridge the gap between fundamental science and cutting-edge computational techniques.

MSc Program Structure


Career opportunities and paths

Graduates of the program may begin an international research career or work with a company (even during the period of study) as the program was developed to meet the high demand for data science specialists in the growing national and international high-tech market. Students gain the opportunity to obtain early access to the national and international research and innovation landscapes and can approach international employers with confidence. In addition, the program enhances students’ soft skills, enabling students to compete effectively in the job market.


Specialist positions such as data analyst, data scientist, consultant in various economy sectors:

  • Finance
  • TeleCom
  • IT


Landing PhD positions and continuing research at leading Russian and international research bodies.


Starting a business on their own or through the Skolkovo innovation ecosystem with its extensive pool of experts, consultants and investors.


The program has a globally renowned faculty with international experience and a broad network of collaborations:

  1. Ivan Oseledets Full Professor
  2. Vladimir Spokoiny Full Professor
  3. Evgeny Burnaev, Associate Professor
  4. Victor Lempitsky Associate Professor
  5. Dmitry Dylov Associate Professor
  6. Dmitry Yarotsky, Associate Professor
  7. Yury Maximov Associate Professor
  8. Mikhail Belyaev Assistant Professor
  9. Gregory Kucherov Leading Research Scientist

Lectures are also delivered by prominent professors including Dr. Denis Belomestny, Dr. Dmitry Vetrov, and Dr. Quentin Paris.

Students are actively involved into research activity starting from Term 3.

Research Areas

  • Industrial Analytics
  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Image Processing
  • High-dimensional statistics and Statistical learning
  • Next Generation Multiscale Modeling
  • Fast Solvers for Large Scale/High-Dimensional Problems

Research Groups

  1. Advanced Data Analytics in Science and Engineering (ADASE) (Prof. Evgeny Burnaev, Prof. Alexander Bernstein) 
  2. Artificial Intelligence in Dynamic Action (Prof. Pavel Osinenko) 
  3. Computational Imaging (Prof. Dmitry Dylov) 
  4. Computer Vision (Prof. Victor Lempitsky) 
  5. Digital Agriculture (Prof. Ivan Oseledets, Prof. Maria Pukalchik) 
  6. Tensor Networks and Deep Learning for Application in Data Mining (Prof. Andrzej Cichocki)
  7. Laboratory of Applied Research Skoltech-Sberbank (Prof. Alexey Zaytsev) 
  8. Machine Learning and Algorithms in Bioinformatics (Prof. Dmitry Yarotsky, Dr. Gregory Kucherov) 
  9. Mobile Robotics (Prof. Gonzalo Ferrer) 
  10. Natural Language Processing (Prof. Alexander Panchenko) 
  11. Statistical Machine Learning (Prof. Maxim Panov) 
  12. Structural Learning (Prof. Vladimir Spokoiny)

Academic Mobility Partners:

  • Aalborg University 
  • Bell Laboratories 
  • Columbia University 
  • Dartmouth College 
  • DLR German Aerospace Center 
  • École Polytechnique Fédérale de Lausanne (EPFL) 
  • ETH Zurich 
  • Facebook 
  • Far East Federal University (FEFU) 
  • Fondazione Bruno Kessler 
  • Jilin University 
  • King Abdullah University of Science and Technology 
  • Massachusetts Institute of Technology (MIT) 
  • New York University (NYU) 
  • Ohio State University 
  • Philips Russia 
  • Technical University of Munich 
  • University of Edinburgh 
  • University of Helsinki 
  • University of Kaiserslautern 
  • University of North Carolina 
  • Wigner Research Center for Physics

Industrial Partners:

  • Sberbank
  • Yandex
  • RusAgro
  • VisionLabs
  • Datadvance
  • ScanEx
  • Geoscan
  • Gazpromneft



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