INFORMATION
SCIENCE
&
TECHNOLOGY
Master of Science
in Information Technology and Engineering
IST program makes a special emphasis on developing hands-on skills in the areas of High Performance Computing (HPC), Big Data, and Internet of Things (IoT), and Advanced Computing and Networks (ACN) which are highly relevant to the emerging field of Industry 4.0. Our graduates will gain knowledge and practical engineering skills in HPC, data management, sensing, and communication.

Skolkovo Institute of Science and Technology
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)
Language:
English
Fees:
no tuition fees for those who successfully pass the selection
Student pack:
monthly stipend (40 000 RUB), medical insurance
Apply before:
The application period is closed. Check again in September.
Education
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 job placement.
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)
IN BRIEF
CURRICULUM
RESEARCH
FUTURE CAREER
ADMISSIONS
A successful graduate of the program will know:
State of the art techniques of scientific computing, including parallel programming and HPC
Cutting-edge Big Data frameworks as well as IoT technologies
Research and applied science methods which respond to the up-to-date business needs
Software, algorithms and tools for HPC, Big Data analysis and IoT systems deployment
Track
Internet of Things (IoT) and Next Generation Wireless Technology
The term "Internet of Things" doesn't have a single definition and people today often use it to interchangeably refer to Wireless Sensor Network (WSN), Machine-to-Machine (M2M), Web of Things (WoT) and other concepts. The focus of IoT Track is to learn about these technologies that will be extending the Internet as we know it and use it today, to interconnect not only people and computers but also sensors and associated objects.

Namely the Track will cover IoT "pillar" technologies including wireless communications, sensing, data and signal processing, and give the opportunity for hands-on sessions where the students will become familiar with the hardware and software supporting the IoT. Apart from covering the theory behind the IoT and "how to connect things to the Internet", the courses will therefore also engage the students to demonstrate the feasibility of simple IoT real applications and will challenge them to improve their applications through the use of cognitive technologies and cloud computing.

This track is also available in a network form with TUSUR (Tomsk), SUAI (St. Petersburg) and Bauman MSTU (Moscow).

A successful graduate of this track will be able to:
  • Use existing IoT technologies to produce applications which leverage on sensed data.
  • Devise solutions for industrial cases (transport, healthcare, agriculture etc.) using IoT.
  • Apply the theory behind the IoT to construct IoT real applications and improve them through the use of smart technologies.
More information about the IoT & Next Generation Wireless Technology track can be found here.
Track
High Performance Computing (HPC) and Big Data
In the modern world one cannot imagine competing in science, business or industry without using powerful supercomputers capable to efficiently handle large scale calculations possibly on exponentially growing amounts of data. The focus of this track is to teach students how to efficiently and easily utilize modern supercomputing and Big Data architectures such as multi-core CPUs and GPUs for various applications in science and industry. Specifically, besides theoretical knowledge about parallel computing and Big Data, students will become familiar with standard parallel computing libraries (such as OpenMP, MPI, OpenACC and CUDA), Big Data frameworks (Hadoop), machine learning frameworks (such as Tensorflow), as well as visualization software (ParaView, Visit).

Additionally, students will be given a possibility to construct their own mini-supercomputer on the hands-on course, and learn how to maintain and administer it. Students will be given a chance of using Skoltech's world-class HPC facilities to learn typical methods and rules of working on the large-scale collectively used supercomputers.

A successful graduate of this track will be able to:
  • Use existing HPC and Big Data frameworks to successfully answer modern world challenges.
  • Develop and optimize massively parallel computer codes capable to efficiently use modern architectures, such as CPUs and GPUs.
  • Administer and maintain HPC and Big Data infrastructure.

More information about the High Performance Computing (HPC) and Big Data track can be found here.
Track
Advanced Computing and Networks (ACN)
(in network form with Lomonosov Moscow State University)
This track develops world-class professionals who specialize in an intersection of areas related to computer networks, the design of complex distributed systems, data processing and analysis, and machine learning. During the studies, the students will be able to collaborate with internationally recognized faculty and scientists of Lomonosov Moscow State University and Skoltech as well as leading global experts in Big Data, complex distributed systems, machine learning, and IoT.

The curriculum is designed in a way that allows students to master state-of-the-art methods and technologies of designing distributed computer systems and networks, modern computing architectures, cloud computing, virtualization, machine and deep learning, distributed algorithms, applied statistics, software protection, and logical verification.

The career path of successful graduates includes cloud architects, cloud system engineers, data scientists, DevOps engineers, Full-stack developers, IoT and network specialists equipped with a wide range of practical skills allowing them to be popular in the labor market.

A successful graduate of this track will be able to:
  • Develop complex distributed computer systems and networks
  • Use cutting-edge network technologies used internationally
  • Create efficient infrastructures for IoT, Big Data, and Data Centers
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.

IoT
Track "Internet of Things (IoT) and Next Generation Wireless Technology"
HPC
Track "High Performance Computing (HPC) and Big Data"
ACN
Track "Advanced Computing and Networks"
IoT
HPC
ACN

Compulsory and Recommended Elective courses (36 credits)
Advanced Computing and Modern Architectures
Specialization in Performance Engineering
Applied Parallel Computing
Computer Networks and Telecommunications (MSU course)
Applied Statistics and Statistical Recognition (MSU course)
Distributed Algorithms and Systems (MSU course)
Software Verification (MSU course)
Seminar: "Distributed Systems and Networks" (MSU course)
Cloud Computing and Resource Virtualization (MSU course)

Elective courses (24 credits)

Entrepreneurship and Innovation (12 credits)
Technological Innovation: from Research Results to Commercial Product

Research and MSс thesis project (36 credits)

Industrial Immersion (12 credits)
Academic Partners:
  • Moscow Institute of Physics and Technology, Russia
  • Keldysh Institute of Applied Mathematics, Russia
  • National Research Center "Kurchatov Institute", Russia
  • Tomsk State University of Control Systems and Radioelectronics (TUSUR), Russia
  • Higher School of Economics, Russia
  • ETHZ, Switzerland
  • Nokia Bell Labs, UK
  • MIT, USA
    Industrial Partners:
    • Sberbank
    • Huawei
    • Yandex
    • Nokia
    • NVidia
    • Datadvance
    • Google
    • Gazpromneft
    • Renova
    • RusAgro
    • Airbus
    • Datadvance
    • TsAGI
    • Schlumberger
    Main research areas:
    IoT

    • Next Generation Communications
    • Coding theory and Digital Signal Processing
    • ML methods in communications
    • Industrial IoT and industrial data processing
    • Sensing and actuation in environmental/industrial/biomedical applications
    • Wearable sensing and wireless sensor networks
    • Embedded AI
    • Post-quantum (code-based) cryptography
    • Information Protection in Computer Systems and Networks
    HPC

    • Mathematical and Supercomputer Modeling
    • Big Data and distributed deep learning
    • Modern Computing architectures and technologies
    • Efficient Numerical Algorithms
    • Computational Complex Systems
      HPC Research groups:

      Our graduates shape their own futures by choosing from a variety of career opportunities
      in industry, science and business:
      Industry
      Landing specialist positions such as Computational Scientist or Engineer in various industry sectors (Aerospace, Advanced Manufacturing, Large-Scale Engineering Design).
      Science
      Landing PhD positions and continuing research at leading Russian and international research bodies.
      Startup
      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.
      Education:
      IT related bachelor's degree, or its equivalent in Mathematics, Computer Science, Information and Communication Technology, Applied Physics 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.
      APPLICATION PACK:
      • Your CV (ENG)
      • Motivation letter (ENG)
      • 2 recommendation letters
      • Diploma or transcript
      • Your certificates and awards, achievements and other materials for portfolio
      Selection process:
      1
      Registration
      Fill out the registration form to start the application process.
      2
      Submit your application
      Familiarize yourself with the list of required supporting documents, upload them into the application system as they become ready and submit your application.
      3
      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.
      4
      In-person interviews (online)
      The final admission stage will take place online. You will need to pass a face-to-face interview, a soft skills challenge and an online Math exam.
      Exam samples:
      Keep in mind that the structure of exam can be changed
      following the decision of program committee.
      Faculty
      The program has a globally renowned faculty with international experience
      and a broad network of collaborations:
      Application
      The application period for Skoltech Master's programs for the 2020-2021 academic year is now closed. To apply for the 2021-2022 academic year, check back in autumn or subscribe below to receive a notification.
      Contact
      e-mail: admissions@skoltech.ru
      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 admissions@skoltech.ru