Computational Science and Engineering
Master of Science Program
The main scope of the CSE program is to train students in using and developing algorithms of scientific computing for applications relevant to the Russian and worldwide industry. The graduates of the program are trained to perform original research in their chosen area of computational science and engineering and apply the results of their research in an industrial context.
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|Modes and duration
Full time: 2 years
No tuition fee for the applicants who pass the selection process
General submission open: December 16, 2016
General submission close: July 16, 2017
First Selection Weekend dates: April 22-23, 2017
Submit your application for the first Selection Weekend till: March 30, 2017
Deadlines for other Selection Weekends will be published after March 30, 2017.
Master of Science in Information Technology and Engineering
|Language of instruction
Program is accredited by the Russian Government, certificate № 1123 from October 13, 2014
Successful candidates must know:
- Ordinary and partial differential equations
- Linear algebra
- General physics
- Programming skills
IT related bachelor’s degree, or its equivalent in Mathematics, Computer Science, Information and Communication Technology, Applied Physics or other technical areas.
|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.
The program focuses on:
• High-performance computing (HPC)
• Modeling and simulations
• Fast and efficient numerical algorithms
• Optimization and uncertainty quantification
Aims and objectives
The curriculum of the program combines state-of-the-art engineering topics (high-performance computing, modern simulation software, etc.) with in-depth teaching of computational science foundations (numerical ODE and PDE, multiscale methods, modeling of stochasticity and Monte-Carlo methods, parallelization strategies). Graduates are expected to possess a combination of deep knowledge of scientific computing background and practical engineering skills (software, algorithms, tools, etc.).
The curriculum of the program contains a balanced combination of topics developed very recently together with in-depth teaching of mathematical foundations.
A successful graduate of the program will know:
- Mathematical and algorithmic foundations of Computational Science & Engineering as well as main aspects of High Performance Computing (HPC).
- Statements of all major computational problems in science and engineering as well as main approaches/techniques to solve them.
- State of the art techniques of scientific computing including parallel programming and HPC.
- Main methodological aspects of both, scientific research and application development in Computational Science and Engineering.
- How to apply different scientific computing techniques and algorithms (including HPC) to real-world problems in natural and social sciences and different industrial sectors.
A successful graduate of the program will be able to:
- Identify, formalize, and solve outstanding computational problems in real-world applications.
- Understand and formulate new models of complex systems arising in natural and social sciences and engineering.
- Choose the most appropriate method to solve a particular computational problem.
- Apply relevant software tools, computer languages, data models, and computational environments for modelling and visualization.
- Contribute in the development of the next-generation scientific computing software competitive with or superior than the existing examples of software in critical and emerging application fields (such as oil and gas, material design, big data, aerospace, and pharma).
- Integrate different components of computational tools and HPC hardware to produce computational solutions for real-world tasks.
- Work with technical literature (e.g. perform an effective bibliographical research, read and critically analyze scientific articles, use scientific metrics and most important databases).
- Communicate results of analysis effectively (visually and verbally) to different audiences (specialists, users, stakeholders etc).
Career opportunities and paths
The CSE MSc program was developed to meet the high demand of computational science and engineering specialists in the growing national and international high-tech market. Graduates of the program may begin an international research career, work with a company or start own company (even during the period of study).
CSE MSc graduates significantly enhance their employability by developing their subject-specific knowledge in the field of computational science and engineering, as well as their analytical and research skills. 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.
- PhD positions in academic & research institutions
- Specialist positions such as Data Analyst, Data Scientist, Consultant in various economy sectors:
- Aerospace, Advanced Manufacturing, Large-Scale Engineering Design
- Oil and gas
- Pharma and Biotech
- Skolkovo resident companies and startups
Professor, Director, Skoltech Center for Computational and Data-Intensive Science and Engineering
- Evgeny Burnaev, Associate Professor
- Andrzej Cichocki, Professor
- Maxim Fedorov, Professor, Director, Skoltech Center for Computational and Data-Intensive Science and Engineering
- Stamatios Lefkimmiatis, Assistant Professor
- Victor Lempitsky, Associate Professor
- Ivan Oseledets, Associate Professor
- Athanasios Polimeridis, Assistant Professor
- Alexander Shapeev, Assistant Professor
- Vladimir Spokoiny, Professor
- Denis Zorin, Adjunct Professor
Students are actively involved into research activity starting from Term 3.
Main research areas:
- Fast Solvers for Large Scale / High-Dimensional Problems
- Next Generation Multiscale Modeling
- Computational Chemistry and Materials Modeling
- Dynamical Systems and Control
- Numerical Optimization
- Computational Prototyping