The program is designed for 3 years with an extension every year. Projects are carried out under the supervision of a professor. From the first year of work, the postdoc has to lead the research team of the project made of postraduate Master and PhD students.
Applications for participation in the competition are accepted until October 26, 2021. The results of the competition will be announced by November 30, 2021.
Feel free to ask question on postdoc program. Phone: +7(863) 218-40-00 ext. 30-010, Alexey Samoylov. Email: info@localhost
|Supervisor||Alexander Bozhenyuk, Doctor of Technical Sciences, Professor. E-Mail firstname.lastname@example.org. Profile in Scopus|
|The goal and objectives of the project||The goal of the research is to develop the theoretical foundations and practical applications of graph neural networks and soft machine learning algorithms for graph analytics and/or computer vision problems. Research objectives: State-of-the-art and open issues in the field of graph and fuzzy neural networks. Research of convolution operations on graphs, deep auto-encoders, vector representations (embeddings). The study of generalized graph structures: hypergraphs and metagraphs. Designing graph NoSQL databases. Research and software implementation of machine and deep learning algorithms.|
|Requirements for an applicant||Knowledge in the field of artificial intelligence methods, graph theory, fuzzy logic, machine learning, and deep learning algorithms. Skills of working with graph databases. Programming skills using machine learning libraries for Python.|
|Participation in educational activities||The applicant will have to develop and implement the Research Frontiers in Artificial Intelligence course (5 credits) for Master students of all ICTIS directions. Content of the discipline: Modern achievements of artificial intelligence: theoretical foundations and practical applications. Generative artificial intelligence. Graph probability models, Bayesian networks. Graph neural networks. Compact representation methods for machine analysis of large volumes of multidimensional data. Methods of knowledge representation and logical inference. New architectures of artificial neural networks. Training of artificial neural networks on limited data sets. Training of artificial neural networks with reinforcement. Improving the methods of teaching artificial intelligence models. Countering malicious effects on AI algorithms.|
|Supervisor||Gennady Veselov, Doctor of Technical Sciences, Professor. E-Mail: email@example.com. Profile in Google Scholar|
|The goal and objectives of the project||The goal of the research is to develop the theoretical foundations and methods of synergetic control of complex systems. Research objectives: analytical review of existing methods of complex system control, development of new methods of intelligent control, control of distributed systems, hierarchical control, group control, control of systems in discrete time.|
|Requirements for an applicant||Knowledge in the field of modern control methods, intelligent control methods, multi-agent systems, the theory of dynamic systems. Skills in software development, synthesis of nonlinear control systems, modeling and research of nonlinear control systems.|
|Participation in educational activities||The applicant will have to develop and implement a course on Synergetic Control Theory (5 credits) for Master students of all ICTIS directions. Content of the discipline: the principle of dynamic expansion-compression of the phase space in control theory, the method of analytical design of aggregated regulators, synergetic synthesis of adaptive control systems, synthesis of discrete control systems, intelligent technologies of synergetic control.|
|Supervisor||Valery Vyatkin, Doctor of Technical Sciences, Professor. E-Mail: firstname.lastname@example.org. Profile in Google Scholar|
|The goal and objectives of the project||The postdoctoral fellow will be involved in research activities focusing mainly on various aspects of modern industrial computing; such as system level design and validation of industrial control and automation systems, simulation and verification and dependable communication.|
|Requirements for an applicant||We expect that a potential candidate would have experience in such priority areas, as multi-agent architectures, flexible production systems, service-oriented architecture, Internet of Things, Semantic Web, programmable logic controllers software (e.g. IEC 61131-3, IEC 61499), distributed programming languages, simulation in the loop, advanced software engineering concepts, formal methods and models.
It is expected that the postdoctoral fellow would have strong software engineering and development skills and would lead a team of master and Ph.D. students.
To qualify for the position of postdoctoral research fellow, an applicant must have a PhD, or doctoral degree or a degree equivalent to a doctorate, in computer science, electrical and computer engineering, industrial automation, or a similar topic.
|Participation in educational activities||The applicant will have to develop and implement a course on Cyber-Physical Systems (5 credits) for Master students of all ICTIS directions. Suggested content: basic concepts and definitions, fundamentals of industrial Internet of Things and cyber-physical systems, multi-agent architectures, design of cyber-physical systems, smart manufacturing.|