Master of Science
in Mathematics and Computer Science
Data scientists are already among the most demanded specialists in the hi-tech market. The goal of this program is to equip the most talented young scientists with high-level knowledge and experience in machine learning, deep learning, computer vision, industrial data analytics, natural language processing, mathematical modelling and other important areas of modern data science.

Skoltech is a new global research university created in collaboration with MIT. The new campus, designed by Herzog de Meuron, is home to 40 world-class labs with best-in-class equipment, globally renowned professors and students from 40+ countries.
Mode, duration:
2 years (full-time)
no tuition fees for those who successfully pass the selection
Student pack:
monthly stipend (40 000 RUB), medical insurance
competitive selection application period for 2022 is now open, the final deadline is on July 10
The MSc program is 2 years long: the first year is to strengthen your theoretical background, and the second year is to focus on research. Students have the freedom to choose courses and extracurricular activities to shape their individual trajectory, acquire soft skills, and gain entrepreneurial skills to prepare for employment.
Lectures and practical classes conducted by world-renowned professors and experts.
Students' individual research projects carried out at Skoltech laboratories.
An 8-week summer industry immersion program at leading companies turning knowledge and skills into action.
Courses on entrepreneurship and innovation that provide skills, as well as knowledge, to commercialize ideas and research findings.
+ Academic mobility at leading global universities (on a competitive basis)
A successful graduate of the program will know:
Mathematical and algorithmic foundations of Data Science
Main methodological aspects of both, scientific research and application development in Data Science
State of the art techniques of machine learning and related areas
Machine Learning and Artificial Intelligence (MLAI)
Machine learning techniques are at the forefront of modern data science and artificial intelligence. The curriculum of the program contains a balanced combination of topics developed very recently together with in-depth teaching of mathematical foundations, such as advanced linear algebra, optimization, high-dimensional statistics, etc.

This track is also available in collaboration with the Moscow Institute of Physics and Technology.

A successful graduate of this track will be able to:
  • understand and formulate complex real-world tasks as data analysis problems
  • contribute to the development of the next-generation machine learning software competitive with or superior to the existing examples of software in critical and emerging application fields
  • apply relevant software tools, algorithms, data models, and computational environments for the solution of real-world problems
Math of Machine Learning (MML)
(in collaboration with Higher School of Economics)
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.

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
    Program structure:
    The 2-year program comprises of compulsory and recommended elective courses on the most important topics, a wide set of elective courses (depending on the research and professional needs of the student), components of entrepreneurship and innovation, research activity and 8 weeks of industry immersion.

    Main research areas:
    • AI & Supercomputing
    • AI for ESG (Environmental, Social and Corporate Governance)
    • AI for Materials Design
    • Computational Imaging & Graphics
    • Computational Intelligence
    • Computer Vision
    • Industrial Analytics
    • Intelligent Signal and Image Processing
    • Machine Learning, Deep Learning & Reinforcement Learning applications
    • Mobile Robotics
    • Medical Computer Vision
    • Mathematical Foundations of AI
    • FinTech
    • Natural Language Processing
    • Quantum algorithms for Machine Learning
    The program is in a network form with:
    • HSE University
    • MIPT
    Industrial Partners:
    • Sberbank
    • Yandex
    • RusAgro
    • VisionLabs
    • Datadvance
    • ScanEx
    • Geoscan
    • Gazpromneft
    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
    Our graduates shape their own futures by choosing from a variety of career opportunities in industry, science and business:
    Landing specialist positions such as Data Analyst, Data Scientist, Industrial Research Scientist, Consultant in various industry sectors (IT, Finance, Telecom and others).
    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.
    Entry requirements:
    Knowledge and skills:
    Calculus, Differential Equations, Linear algebra, Probability theory and mathematical statistics, Discrete mathematics (including graph theory and basic algorithms), Programming.
    Bachelor's degree or its equivalent in Mathematics, Computer Science, Information and Communication Technology, or other technical areas.
    English Language:
    If your education has not been conducted in English, you will be expected to demonstrate evidence of an adequate level of English proficiency.
    • Your CV (ENG)
    • Motivation letter (ENG)
    • 2 recommendation letters
    • Diploma or transcript
    • Your certificates and awards, achievements and other materials for portfolio
    Selection process:
    Prepare your portfolio
    Prepare your competitive selection application materials.
    Submit your application
    Upload your materials into the application system and submit your application.
    Online testing
    Every candidate must take an online profile test. You will be notified by email about the specific date and time of your test.
    In-person interviews
    The final selection stage takes place in Moscow. You have to pass the English exam on site, or present a valid proof of English proficiency, pass an in-person interview and entrepreneurship challenge. Extra written examinations may be required for certain programs during this time (you will be notified in advance). In case you're not from Moscow, we can accommodate you in the Skoltech dorms for the selection weekend period.
    Exam samples:
    Keep in mind that the structure of exam can be changed
    following the decision of program committee.
    Tips on Math Examination
    The goal of the Math Examination is to assess ADVANCED math abilities of MSc applicants in calculus, linear algebra, differential equations, and probability. The math exams typically include several problems on topics studied in standard undergraduate mathematical courses (see example). Below we list them along with examples of well-known textbooks:

    • M. Spivak. Calculus (1994)
    • S. Lang. A first course in calculus (1986)

    Linear algebra
    • S. Lang. Linear Algebra (1987)
    • Sh. Axler. Linear Algebra Done Right (2015)

    Ordinary differential equations
    • M. W. Hirsch, S. Smale. Differential Equations, Dynamical Systems, and Linear Algebra (1974)
    • V. I. Arnold. Ordinary differential equations (1973)

    • H. Tijms. Understanding Probability (2007)
    • Sh. Ross. A first course in probability (2019)
    what our students say
    The program has a globally renowned faculty with international experience and a broad network of collaborations:
    Instructors at HSE University
    Research / Labs
    Every program dedicates time for students' independent research as a core part of their curriculum. Skoltech hosts more than 25 world-class laboratories. Students have full access to the facilities throughout their studies and can conduct research based on their interests.

    Feel the spirit of Skoltech campus and take a look inside data science labs.
    Click the button "Begin" to start preparing your application to Skoltech. We will send you an email with all the necessary information.

    Or go straight to SIA if you know how to fill out an application form or if you already have an account:)

    Hurry up, the final deadline is on July 10!
    Start your Skoltech journey!
    Submit the form below and we will send you all the necessary information about getting to Skoltech
    First name
    Last name
    Telephone number
    Country of citizenship
    Country of citizenship
    Educational program
    Educational program
    By submitting your information, you are agreeing to Skoltech's Personal Data policy.
    Subscribe to Skoltech's newsletter
    Receive university news, invitations to exclusive events and student life updates in your inbox.
    First name
    Last name
    By submitting your information, you are agreeing to Skoltech's Personal Data policy.
    phone: +7 (495) 280-1481_ext.3387
    address: 30с1 Bolshoi boulevard, Skolkovo, 121205, Russian Federation, Room E-R3-2030

    We are more than happy to meet visitors Monday to Friday from 9:00 to 18:00. Please arrange a visit 48 hours in advance by contacting
    Subscribe to Skoltech's newsletter
    First name
    Last name
    By submitting your information, you are agreeing to Skoltech's Personal Data policy.