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Education, research and development in the field of IT and Robotics
World-class IT education in Russia in English
Innopolis University has 17 laboratories and 9 research centers, which conduct research in the field of artificial intelligence, robotics, big data, software development, information security
The university’s project-based activities are aimed at implementing grant-based and commercial projects, as well as at enhancing the availability of education in IT areas.
Education, research and development in the field of IT and Robotics
The program is offered to candidates interested in Research & Development, with fundamental knowledge in mathematics and skills in information search and reporting. The program enables graduates to respond to professional responsibilities that include preliminary data processing, big data management, application of machine learning algorithms, data analysis and reporting.
Duration: 1 year of study + 1 year of practice
Start of studies: mid-August
Language of tuition: English
• development of modern machine learning models
• applying modern machine learning approaches to scientific and engineering problems
• understanding received data
• data analysis
• research activities in the field of data analysis and/or machine learning
Artificial Intelligence Centre (AIC) - one of the technology centers of Innopolis University.
Competencies of the center in the field of AI:
• Machine learning (neural networks, deep learning);
• computer vision;
• natural language processing;
• big data analysis;
• systems of recommendations and assistance in making decisions.
The specialists of the center carry out scientific activities (fundamental and interdisciplinary research), develop solutions based on artificial intelligence for various tasks and industries, conduct a technical audit regarding the potential for the implementation of AI solutions, and also train personnel within the framework of specialized programs (additional industry education and professional development ).
Professor, Head of the Laboratory of machine learning and knowledge representation
Courses taught: Machine Learning
Directions of scientific work:
• GAN training with a fraction of data
• Domain adaptation
• Data warehouse
• High-performance computing
Courses taught: Empirical Methods, Advanced Statistics
Directions of scientific work:
• Analysis of the work of the brain while programming
• Analysis of software engineering metrics
• Profiling domains for exploring product features
• Interactive guide for agile/lean software development
Courses taught: Software Design with Python
Directions of scientific work:
• Compiler construction
• Simulation systems
Assistant Professor, the Laboratory of Industrial Production of Software
Courses taught: Managing Software Development
Directions of scientific work:
• Natural language processing for cyber-security requirements analysis
• Object-oriented requirements and cyber-security testing
Courses taught: High-dimensional Data Analysis
Directions of scientific work:
• Computational modeling in molecular biology
• Traffic modeling
PostDoc, the Laboratory of Industrial Production of Software
Courses taught: Empirical methods
Directions of scientific work:
• Automatic classification of user activities by application in use
• Automatic calculation of code/project metrics from open-source repositories
• User presence identification based on I/O signal analysis
Assistant Professor, the Laboratory of machine learning and knowledge representation
Courses taught: Advanced Information Retrieval
Directions of scientific work:
• Quantum Machine Learning
• Visual tools for textual dataset exploration
• Computer vision
• Data Structures
Our graduates hold the following positions:
• machine learning developer (middle/senior level)
• data scientist
• data analysis specialist
• analyst
• data engineer
And hold these positions in the following companies:
• Yandex
• Tinkoff
• ICL
• Kontur
• S7
partial grants available
accommodation fee/month
tuition fee
01
Register in the admissions portal account, fill in an application form with all mandatory fields, take tests and click “SUBMIT” to complete the application.
Selection criteria at this stage:
— Technical university degree
— Expertise in mathematics (entry tests)
— English language proficiency (intermediate level or higher)
Practical experience in data analysis will be an advantage.
02
Successful applications are selected for further consideration. We would like to see the candidates with strong expertise in physics and mathematics, programming, which can be applied in solving real practical tasks. Knowledge of robotics is not compulsory.
Selection criteria at this stage:
— Strong fundamentals in mathematics (linear algebra, mathematics)
— Programming skills (Python)
— English language proficiency
— Motivation and personal skills
02
Successful applications are selected for further consideration. We would like to see the candidates with strong expertise in physics and mathematics, programming skills, and ability to implement them at solving practical tasks. Knowledge of robotics is not compulsory.
Selection criteria at this stage:
— Strong fundamentals in mathematics (linear algebra, mathematical analysis, differential equations, probability theory, statistics)
— Understanding of physics and its processes (mechanics)
— Programming skills (low level or/and high-level programming languages)
— English language proficiency
1. Professional testing:
- Mathematical test (mathematical analysis, linear algebra, discrete mathematics, probability theory and statistics)
- Algorithms and data structures, programming.
2. English language testing
You can confirm English proficiency in one of the following ways:
- providing an international English language test certificate (IELTS, TOEFL (including TOEFL iBT Special Home Edition)),
- taking IU extended English test (free of charge), OR
- providing an official letter from your School/University stating that the studies were delivered in English.
This is a technical interview with questions on practical experience, on the basics of Computer Science (CS): algorithms, data structures, theory of automata, networks, etc.
This interview aims to identify your personal qualities. During the conversation, you may be asked questions about your motivation, study and work, and others.
03
Get the offer by email and confirm it. Provide all enrollment and visa documents, pay tuition fee (for Partial Grant candidates) and come to Innopolis in mid-August.
420500 Innopolis, Russia 1, Universitetskaya Str.
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