PhD courses
Speciality Code:
8D06105
Speciality Name:
Systems Engineering
Faculty:
Information technology
Qualification:
- Scientific and pedagogical direction - Doctor of Philosophy (PhD)
- Model of graduating student
- Mandatory disciplines
- Elective disciplines
- Professional
ON1 Outline the basic principles of design and management of large-scale engineering systems throughout the life cycle, demonstrate an interdisciplinary understanding of the concepts of systems;
ON2 Use tools from a variety of areas, including management systems, operations research, reliability and performance, risk analysis, software development, and networking and security when planning research and computing experiments;
ON3 Conduct a critical analysis, evaluation and selection of elements of system engineering, methods and standards, architecture, computer tools that support system engineering, with a view to their further application in the development of large-scale engineering systems;
ON4 Solve the problem of risk assessment, costing, management of engineering programs;
ON5 Consider and integrate all possible aspects of a project or system, such as requirements development, reliability, logistics, coordination of different groups, testing and evaluation, maintainability;
ON6 Apply various methods of modeling engineering systems, as well as methods of numerical and computer solutions used in industrial and engineering environments;
ON7 To critically analyze, evaluate and synthesize new complex ideas that are at the very forefront of science in professional activity;
ON8 To generate new and complex goals, to propose new hypotheses and solutions of scientific problems in the field of system engineering based on an independent original approach;
ON9 Plan and carry out educational and training activities in higher education organizations using traditional, innovative, interactive, student-centered technologies and teaching methods;
ON10 To build a research process on the topic of the thesis, to present scientific results in a reasoned and reasonable manner for discussion in scientific discussions and publications in national and international peer-reviewed publications;
ON11 To present the results of educational and research activities in the form of scientific reports, theses of articles, doctoral dissertations, educational research and scientific projects;
ON12 To be ready for correct and tolerant interaction in society, for teamwork, for social interaction and cooperation for solving scientific and technical problems.
ON2 Use tools from a variety of areas, including management systems, operations research, reliability and performance, risk analysis, software development, and networking and security when planning research and computing experiments;
ON3 Conduct a critical analysis, evaluation and selection of elements of system engineering, methods and standards, architecture, computer tools that support system engineering, with a view to their further application in the development of large-scale engineering systems;
ON4 Solve the problem of risk assessment, costing, management of engineering programs;
ON5 Consider and integrate all possible aspects of a project or system, such as requirements development, reliability, logistics, coordination of different groups, testing and evaluation, maintainability;
ON6 Apply various methods of modeling engineering systems, as well as methods of numerical and computer solutions used in industrial and engineering environments;
ON7 To critically analyze, evaluate and synthesize new complex ideas that are at the very forefront of science in professional activity;
ON8 To generate new and complex goals, to propose new hypotheses and solutions of scientific problems in the field of system engineering based on an independent original approach;
ON9 Plan and carry out educational and training activities in higher education organizations using traditional, innovative, interactive, student-centered technologies and teaching methods;
ON10 To build a research process on the topic of the thesis, to present scientific results in a reasoned and reasonable manner for discussion in scientific discussions and publications in national and international peer-reviewed publications;
ON11 To present the results of educational and research activities in the form of scientific reports, theses of articles, doctoral dissertations, educational research and scientific projects;
ON12 To be ready for correct and tolerant interaction in society, for teamwork, for social interaction and cooperation for solving scientific and technical problems.
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Academic writing
- Number of credits: 2
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: The purpose of studying the discipline: to acquire the necessary knowledge and skill for academic writing at the PhD level. This course deals with three main issues of academic writing of students: 1. the writing of academic texts in system engineering; 2. the writing of scientific articles in English to foreign magazines; 3.the writing of a doctoral dissertation. As a result of the course, the doctoral student develops and forms an exact, clear, compact, and objective academic writing style in system engineering
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Large-scale high performance computing systems
- Number of credits: 5
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: The purpose of discipline:is to build the ability to implement parallel and distributed algorithms, run them in real high-performance computing systems. As a result of studying the discipline, the following abilities of doctoral students will be formed: - develop, implement and analyze parallel algorithms; - perform computations in modern HPC systems, such as OpenMP on shared memory nodes, CUDA for graphics coprocessors, and MPI and PGAS models for distributed memory systems; - develop scalable parallel algorithms that are effective in increasing the size of the problem and effective in increasing the size of the system; - analyze the possibilities for reducing the asymptotic complexity of tasks, reducing communications and data movement; - develop and analyze algorithms for three main classes of computing systems: multi-core with shared memory, systems with distributed memory, such as clusters and supercomputers, sequential or parallel systems with deep memory hierarchies. Within the discipline the following aspects will be considered: Introduction to the HPC architecture and parallel programming. Basic architecture and organization: hierarchy of memory, architecture with distributed and distributed memory, multiprocessor architecture. Introduction to concurrency at the thread level. Accelerators (GPU, Xeon-Phi). Prediction and evaluation of effectiveness. Parallel programming / computing: an introduction to MPI / OpenMP, the basics of CUDA programming. Optimization of cluster work: execution of tasks in the HPC environment, task scheduler, load balancing at the cluster level. Open source software. Software parallelization: domain / spatial decomposition, uncoupled interaction distribution, dynamic load balancing, multiprocessor communication.
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PhD thesis writing and defence
- Number of credits: 12
- Type of control: Докторская диссертация
- Description: The main purpose of "PhD thesis writing and defence": of a doctoral dissertation is the formation of the doctoral students' ability to disclose the content of research work for the defense of the thesis. During the study of course, doctoral student's should be competent in: 1. to substantiate the content of new scientifically grounded theoretical and experimental results that allow to solve a theoretical or applied problem or are a major achievement in the development of specific scientific directions; 2. explain the assessment of the completeness of the solutions to the tasks assigned, according to the specifics of the professional sphere of activity; 3. they can analyze alternative solutions for solving research and practical problems and assess the prospects for implementing these options; 4. apply the skills of writing scientific texts and presenting them in the form of scientific publications and presentations. 5. to plan and structure the scientific search, clearly highlight the research problem, develop a plan / program and methods for its study, formalize, in accordance with the requirements of the State Educational Establishment, the scientific and qualification work in the form of a thesis for a scientific degree Doctor of Doctor of Philosophy (PhD) on specialty «8D07502 – Standardization and certification (by industry)». During the study of the discipline doctoral student will learn following aspects: Registration of documents for presentation of the thesis for defense. Information card of the dissertation and registration-registration card (in the format Visio 2003). Extract from the minutes of the meeting of the institution, in which the preliminary defense of the thesis took place. Cover letter to the Higher Attestation Commission. Expert conclusion on the possibility of publishing the author's abstract. Expert opinion on the possibility of publishing a dissertation. Minutes of the meeting of the counting commission. Bulletin for voting. A shorthand record of the meeting of the dissertational council. List of scientific papers. Response of the official opponent. A review of the leading organization. The recall of the scientific adviser.
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Scientific Research methods
- Number of credits: 3
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: In this course, we understand and master the research methodology used in IT. The course will cover topics ranging from the principles of experiment design, statistics, to various aspects of reading, evaluating scientific papers, and presenting research results. There will be assignments allowing the students to practice different research skills and methodologies covered in the lectures. The students will be select sources, design and determine the execution algorithms and make predictions to their doctoral research project, and present research proposal.
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Object-oriented paradigm
- Number of credits: 5
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: The purpose of discipline: formation of the ability to build a solution to large-scale problems using an object-oriented paradigm. As a result of studying the discipline, the following abilities of doctoral students will be formed: - use the advantages and critical attributes of an object-oriented approach to the development of window and web applications; - apply key attributes of software analysis / design tools; - reuse program code, components and modules; - construct diagrams using the graphic description language for UML object modeling for various design stages; - develop object-oriented models for software development. Within the discipline the following aspects will be considered: Object-oriented software development. Object Oriented Modeling with UML. Object-oriented programming, model encapsulation, information hiding, polymorphism, inheritance. Documenting code. Unit testing Graphic user interface. Designing and developing software using the principles of modularity, encapsulation, information hiding, abstraction, and polymorphism.
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Programming in computer systems
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: The purpose of the discipline is to form the ability to use computing equipment, system software in science and technology for solving practical problems. Upon successful completion of this module, doctoral students should be able to: - describe ways of developing system software, taking into account the hardware and software features; - perform the debugging and testing of software products; - develop software modules in modern programming languages; - implement debugging and testing programs at the module level; - analyze the correctness and computational complexity of algorithms and programs. Mastering the main type of professional activity. The main approaches to programming in computer systems. Work with the file system and character input and output. Work with the registry. Exception Handling. Memory management. Dynamically compiled libraries. Process management. Flows and execution planning. Synchronization of threads. Interaction between processes. Debugging software modules using specialized software. Testing software modules.
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Applied software development
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: The purpose of discipline:formation of the ability to perform group projects, in which doctoral students must work with an external client to develop and release a working application. As a result of studying the discipline, the following abilities of doctoral students will be formed: - design and implement object-oriented programs, effectively using a large selection of libraries; - use programming tools such as integrated development environment, debugger and code repository; - develop, document and implement software for a real client application, which could be a mobile application, a cloud application or a web service; - design and implement graphical user interfaces suitable for scaling across multiple devices and resolutions; - apply effective teamwork methods and project organization skills. Within the discipline the following aspects will be considered: Models of software processes. Rational single process. Agile software development. Scaling flexible methods. System modeling. Model-oriented design. Software development, implementation, testing. Open source development. Software testing. The evolution of software. Software maintenance. Component software engineering. Types of component composition. Distributed software development. Aspect-oriented software development.
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Computer Systems Reliability and Fault Tolerance
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: The purpose of discipline: formation of the ability to apply methods and technologies for assessing the reliability of elements and systems in the study and design of modern computer systems. As a result of studying the discipline, the following abilities of doctoral students will be formed: - describe methods and technologies for assessing the reliability of computer system elements; - perform the formal formulation of tasks arising from the increase in the reliability of computer systems; - develop an algorithm for solving the problem on the basis of the most appropriate method for assessing the reliability and fault tolerance of computer systems; - implement the developed algorithm using programming languages; - analyze the correctness and computational complexity of algorithms and programs. Within the discipline the following aspects will be considered: The problem of reliability in the modern world. Evaluation of the reliability of non-recoverable systems of various configurations. Quantitative indicators of reliability. Continuous and discrete laws of reliability. Related distributions. Accelerated reliability tests. Calculation of reliability in terms of incomplete information. Bayesian approach. Reliability of non-recoverable systems. Calculation using logical algebra. Redundancy as a method of improving reliability. The choice of elements and schemes. Optimization of the cost of reserved objects. Reliability of the restored systems. Calculation of availability factors. Software reliability assessment. Control, refinement and acceptance of programs. Service reliability in enterprises. Tasks. Structure and documents.
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Computer Modeling
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: The purpose of discipline:formation of the ability to apply various methods of modeling engineering systems, as well as methods of numerical and computer solutions used in industrial and engineering environments. As a result of studying the discipline, the following abilities of doctoral students will be formed: - perform numerical modeling of linear and nonlinear ordinary differential equations and deterministic systems; - predict the behavior of the model based on new input data and validation of the output data; - plan and carry out assessment tasks based on research, with a creative approach and initiative in new situations in professional practice and with a high level of personal autonomy and accountability; - develop creative and innovative solutions to engineering problems; - create system reports and system specifications in a simulation environment. Within the discipline the following aspects will be considered: The main aspects of modeling and simulation. Modeling process. Models and systems. Statistical problems associated with modeling. Discrete and continuous simulation. Modeling applications. Introduction to the software modeling environment. Network modeling Basic technology modules. Simulation of detailed operations. Decision making through simulation. Modeling processes. Advanced modeling techniques. Analysis of the modeling process. Costing and animation.
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Database systems design technologies
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: The purpose of discipline:formation of the ability to create database systems with a focus on technologies such as sensor networks, personal databases and information management on the Internet. As a result of studying the discipline, the following abilities of doctoral students will be formed: - set out the fundamental theoretical and methodological provisions for the academic study of database design technologies, including some of the most important and relevant scientific works; - handle scientific articles in this area; - plan and carry out the research process with the requirements of scientific certainty; - select technology, software and computer equipment for analyzing database system design technologies; - develop components for intelligent problem solving or decision making, components for specialized data processing, and components for managing general information. Within the discipline the following aspects will be considered: The evolution of the database system. Relational database systems. Information integration. Transaction processing Relational data model. Determining the relationship schema in SQL. Algebraic query language. Relationship restrictions. Design theory for relational databases. Rules about functional dependencies. High level database models. From UML diagrams to relationships. Programming relational databases. Relational algebra and data log. Representations and indexes. Stored procedures. Modeling and programming of semistructured data.
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Management of IT infrastructure and services
- Type of control: [RK1+MT+RK2+Exam] (100)
- Description: The purpose of discipline:formation of the ability to create IT management systems and services based on modern technologies. As a result of studying the discipline, the following abilities of doctoral students will be formed: - to process scientific articles in the field of IT infrastructure management; - to analyze the latest advances in the management of IT infrastructure and services presented in modern research; - plan and carry out a research process taking into account the requirements of the scientific field; - select technologies, software and computer equipment for analyzing the management of IT infrastructure and services; - organize effective interaction with the scientific community in the creation and dissemination of research and development, high-tech products. Within the discipline the following aspects will be considered: Service strategy. Key ideas. Key processes and activities. Designing services. Moving services. Service management. Continuous improvement service. Processes and service management functions. Cloud computing standards. The strategic implications of cloud computing. Cloud architecture. Cloud computing modeling. Cloud computing design. Types of distributed systems. Analysis of IT infrastructure management.
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Pedagogical
- Type of control: Защита практики
- Description: Aim оf discipline: formation of the ability to carry out educational activities in universities, to design the educational process and conduct certain types of training sessions using innovative educational technologies.
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Research
- Type of control: Защита практики
- Description: The purpose of the practice: gaining experience in the study of an actual scientific problem, expand the professional knowledge gained in the learning process, and developing practical skills for conducting independent scientific work. The practice is aimed at developing the skills of research, analysis and application of economic knowledge.