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.
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Key information |
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Program starts |
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Modes and duration |
Tuition fees |
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Awarded degree Field of Science and Technology |
Language of instruction |
Accreditation |
Entry requirements Bachelor’s degree or equivalent in Mathematics, Computer Science, Physics, Chemistry, or Engineering. Knowledge and skills: Calculus, Differential Equations, Linear algebra, Probability theory and mathematical statistics, Numerical methods. |
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English language requirements |
Aim and objectives
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:
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:
Track
FinTech (Applied Artificial Intelligence and Mathematical Modelling in Economics and Finance)
taught in collaboration with the New Economic School faculty
Combining the exceptional foundational education from the prestigious New Economic School with state-of-the-art methods in machine learning and data analysis, this track offers a unique fusion of knowledge. Be at the forefront of innovation by mastering the tools and techniques that drive the financial industry forward.
In collaboration with Sber, Russia’s leading bank, our program benefits from their expertise and involvement in shaping the curriculum. Gain valuable insights and work on cutting-edge projects, including the opportunity to undertake impactful master’s theses in collaboration with Sber.
The track encompasses a wide range of courses, ensuring a holistic and well-rounded learning experience. From mathematics and data science to economics and finance, you will gain multidisciplinary knowledge essential for success in the financial industry. Explore specialized topics such as Bayesian Methods of Machine Learning and Financial Analysis and Accounting. Find more details about this track in the brochure.
MSc Program Structure
Career opportunities and paths
Faculty
Program Director ![]()
Nikolai Brilliantov
Full Professor
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Program coordinator ![]()
Vladimir Palyulin
Associate Professor
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Research
Students are actively involved into research activity starting from Term 3.
Main research areas:
Research groups:
Academic Partners:
Moscow Institute of Physics and Technology, Russia
Industrial partners:
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