Introduction
Overview
Modern science and engineering critically rely on efficient and fast computational techniques and models. ACS program achieves the synergy of state-of-the-art mathematical modeling methods (numerical ODE and PDE, stochastic modeling, machine learning, and Big data-based approaches) and their implementation with modern high performance parallel computational facilities furnished with up-to-date software. The cutting-edge scientific MSc project solidifies the theoretical knowledge obtained in the courses.
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 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.
© The Skolkovo Institute of Science and Technology (Skoltech)
In brief
A successful graduate of the program will be capable of:
Handling the available information about real-world tasks and shaping it into a form of efficiently solvable mathematical models;
Developing new computational approaches and algorithms for data-intensive problems;
Using High-Performance Computing techniques in Python and C/C++ to develop and/or optimize massively parallel computer codes;
Utilizing modern frameworks for data visualization.
Program structure
The 2-year program comprises 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.
Track: Data-Intensive Mathematical Modelling and Simulations (DIMMS)
This track aims at fostering a new generation of computational scientists and engineers, able to combine first principle and data-driven approaches in mathematical modeling of natural, industrial and social phenomena. The curriculum carefully balances advanced computing, machine learning, and computational physics to implement large scale models in modern computational environments.
A successful graduate of this track will be able to:
Construct mathematical models of industrial processes, natural, and social phenomena based on fundamental principles and available data;
Contribute to the development of efficient algorithms and codes for computationally demanding, data-intensive modeling and simulations;
Apply relevant computational approaches, data structures, hardware, and software to complex real-world problems.
Track: High-Performance Computing (HPC) and Big Data
The modern computational world is essentially parallel as CPUs and GPUs contain multiple cores. Datasets and computational problems are becoming impossible to be processed using a single compute node.
Besides pursuing an academic career, HPC track students with knowledge of modern computing architectures, programming, code optimization, and distributed deep learning will easily find Data Scientist, Software Engineer, or IT-specialist positions in various industries, including IT, Oil & Gas, Finance & Banking, Industrial R&D, Manufacturing and more.
A successful graduate of this track will be able to:
Effectively address modern computing world challenges using existing and state-of-the-art HPC and Big Data frameworks in a variety of applications (deep learning, data analytics, mathematical modeling of complex events);
Solve mathematical modeling and data-intensive tasks using parallel computing;
Develop and optimize massively parallel computer codes;
Create efficient infrastructures for HPC clusters, Big Data, and Data Centers.
Future career
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 Data Analyst, Data Scientist, Industrial Research Scientist, Consultant in various industry sectors (Сhemical and Pharmaceutical industry, Oil & Gas, IT, Finance, and others).
Science
Landing Ph.D. 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, Numerical methods. High level of English proficiency.
Programming skills: C/C++, Fortran, MATLAB, Python, Julia (at least one of the mentioned languages).
Education: Bachelor's degree or equivalent in Mathematics, Computer Science, Physics, Chemistry, or Engineering.
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
© The Skolkovo Institute of Science and Technology (Skoltech)
