Digital Materials Science (AES)

In recent years, computer modeling has made significant strides in the field of materials science. It is now possible to predict the properties of new materials even during the development stage, significantly reducing the time needed to find and test them in the commercial market. Within the framework of the Advanced Engineering School “Materials Science, Additive and Cross-Cutting Technologies” (AES MACT) we have created a Master’s program that trains specialists in digital materials science. These specialists are able to use advanced tools to develop new materials. Thanks to scientific approaches and computing power of computers, students will be able to use innovative modeling methods in materials science, which allows them to predict the structure and properties of materials on a computer before they are synthesized or tested in a physical experiment.

2 years of study

Full-time education in Russian

Major # 22.04.01
Materials Science &Technologies

425 000 ₽

Admissions

Details of admission

E-mail: welcome@misis.ru

International Students Service +7 499 649-44-80

Personally: Moscow, Leninsky Prospekt 4, block 1 (main building), 1st floor

Key Disciplines

15
subjects in the field of computer materials science

Key disciplines:

Data Analysis and Machine Learning

Quantum Mechanical Calculations

Basics of Programming

Computational Thermodynamics

Computer-aided Design of Materials

Quantum Computers in Materials Science

Teachers

Alexey Vitalievich Yanilkin

Head of Department at the All-Russian Scientific Research Institute of Automation (VNIIA)

Research interests: multiscale approaches, search for new materials, materials informatics, structural materials, functional materials, reactor materials science, solid state physics, condensed matter physics, chemical physics. Number of publications — 89 (Scopus). Hirsch index — 20 (Scopus).

yanilkin@vniia.ru

Ivan Alexandrovich Kruglov

Research interests: Prediction of the structure of stable materials, machine learning methods, materials informatics. Number of publications — 42 (Scopus). Hirsch index — 19 (Scopus)

ivan.kruglov@phystech.edu

Pavel Yurievich Korotaev

Research interests: machine learning methods, materials informatics, quantum mechanics, solid state physics, condensed matter physics. Number of publications — 18 (Scopus). Hirsch index — 7 (Scopus).

korotaev@vniia.ru