Overview
The PhD program in Electrical Engineering (further in the text: PhD program), fully taught in English, is designed to provide advanced skills and a sophisticated knowledge base at the expert level for individuals planning a career in academia, industry and research settings in any of the subfields of the Electrical engineering discipline. The program focuses on the development of an in-depth understanding of the nature, implementation and evaluation of Electrical engineering principles and applications together with the growth of research skills. The current areas of research interest for the PhD in Electrical Engineering encompass a wide spectrum, with specific focus on priority areas for Kazakhstan, such as: power engineering; electronics, signal processing and communication, biomedical engineering, intelligent mechatronic systems, computer engineering.
These areas are also aligned with well-known international research priorities, such as: Leadership in Enabling and Industrial Technologies (Information and Communication Technologies; Nanotechnologies; Advanced Materials; Advanced Manufacturing and Processing); Environment, Future and Emerging Technologies; Health, demographic change and wellbeing (Improving diagnosis; Innovative treatments and technologies; Integrated, sustainable, citizen-centered care).
By the completion of the PhD program, students will be capable of designing and conducting independent, innovative, original and high-quality research related to a variety of topics in Electrical engineering. In addition, the program will prepare graduates for careers in an industrial and academic environment in the positions of university faculty members, senior researchers, engineers; and product developers.
The PhD program has been designed in line with the revised Graduate Programs Framework of Nazarbayev University.
These areas are also aligned with well-known international research priorities, such as: Leadership in Enabling and Industrial Technologies (Information and Communication Technologies; Nanotechnologies; Advanced Materials; Advanced Manufacturing and Processing); Environment, Future and Emerging Technologies; Health, demographic change and wellbeing (Improving diagnosis; Innovative treatments and technologies; Integrated, sustainable, citizen-centered care).
By the completion of the PhD program, students will be capable of designing and conducting independent, innovative, original and high-quality research related to a variety of topics in Electrical engineering. In addition, the program will prepare graduates for careers in an industrial and academic environment in the positions of university faculty members, senior researchers, engineers; and product developers.
The PhD program has been designed in line with the revised Graduate Programs Framework of Nazarbayev University.
General information
- Campus: Astana, Kazakhstan
- Language: English
- Delivery mode: Full time, on-campus
- Duration: 4 years
- Total ECTS credit: 240
Program Aims
The program aims to prepare:
- The overarching aim of the program is to develop high-quality doctoral researchers who are ready and able to make a lasting contribution to addressing scientific, technological, economic, societal and environmental challenges of global significance. It is closely associated with the aim of Kazakhstan to increase its global competitiveness and join the top 30 most developed countries in the world by 2050. The program aims to prepare: specialists for advanced careers in (national and multinational) industry and academia in Kazakhstan, in neighboring countries and internationally.
- Future policy and decision-makers for careers in governmental agencies, public service, and the social economy, in Kazakhstan, and globally.
- Entrepreneurs who will be able to promote advanced and innovative science-rich technologies anywhere in the world.
- New generation of commercially aware and technologically advanced scientists and technologists to lead future developments in the chosen electrical engineering sub-discipline.
- Future academics and researchers in electrical engineering sub-disciplines for careers as specialists in universities of Kazakhstan and other parts of the world.
Key Advantages
- Expert-level doctoral educationdesigned for advanced careers in academia, research, industry, technology development, and public-sector leadership.1
- Strong focus on original and independent researchenabling students to generate new knowledge and make a significant contribution to a specialised area of electrical engineering.2
- Research aligned with Kazakhstan’s technological prioritiesincluding power engineering, electronics, signal processing and communications, biomedical engineering, intelligent mechatronic systems, and computer engineering.3
- Flexible and individually tailored study pathwaythrough doctoral-level electives selected according to the student’s research topic and approved by the supervisory committee.4
- Advanced technical preparationin system modelling and control, algorithms, signal processing, electronic circuits, semiconductor technologies, stochastic processes, energy systems, and machine learning.5
- Continuous research development throughout the programmeincluding literature analysis, research planning, experimentation, data interpretation, publication, and dissertation preparation.6
- Individual supervision by a multidisciplinary committeeincluding a lead supervisor, an internal co-supervisor from Nazarbayev University, and an external co-supervisor from outside the University.7
- Strong publication and scholarly communication requirementspreparing students to publish original research, present their findings, and participate in national and international academic networks.8
- Teaching and academic experiencethrough participation in the University’s teaching mission as a Graduate Teaching Assistant.9
- International and industry exposureincluding research and development links with external organisations and the opportunity to complete a three- to twelve-month research internship at an approved international host institution, subject to funding and programme approval.10
Learning Outcomes
Upon successful completion of this program, students will be able to:
- Review, analyse, and evaluate the body of scientific literature in their field of study in Electrical Engineering.
- Identify appropriate research topics in their field of study in Electrical Engineering, and generate hypotheses about such topics.
- Plan, develop, analyse and communicate research in writing and verbally independently.
- Make an original contribution to the knowledge in their area of specialization within Electrical Engineering.
- Judge technically and ethically and relate their research to the broader field of knowledge in their Electrical Engineering sub-discipline.
- Develop their academic/scholarly career through presentations, publications, and national and international networking.
What Will You Learn?
- Academic writing, peer review, and scientific communication
- Experimental design, data collection, and research validation
- Research-problem identification and hypothesis development
- Advanced system modelling and control
- Research methodology and research ethics
- Stochastic processes and statistical modelling
- Pattern recognition and machine learning
- Independent research and dissertation development
- Advanced electronic circuits and systems
- Semiconductor fabrication and VLSI technologies
- Industrial and commercial energy systems
- Digital signal processing and optimal filtering
- Critical analysis of scientific literature
- Advanced data structures and algorithms
Curriculum
¹ Course may be waived for NU graduates and replaced by a Level-8 course (core or elective) selected by the student’s supervisory committee and approved by the corresponding departmental committee.
² 0 ECTS credited if the thesis is not completed / defended in that semester.
³ If not submitted / defended, the requirement carries forward to the following semester.
² 0 ECTS credited if the thesis is not completed / defended in that semester.
³ If not submitted / defended, the requirement carries forward to the following semester.
Elective Courses
DELCE 760 - Advanced System Modelling and Control
DELCE 761 - Advanced Data Structures and Algorithms
DELCE 762 - Fundamentals of Signal Processing
DELCE 763 - Advanced Electronic Circuits
DELCE 764 - Advanced Semiconductor Process Engineering for VLSI
DELCE 760 - Advanced System Modelling and Control
DELCE 761 - Advanced Data Structures and Algorithms
DELCE 762 - Fundamentals of Signal Processing
DELCE 763 - Advanced Electronic Circuits
DELCE 764 - Advanced Semiconductor Process Engineering for VLSI
Core modules
The list of core modules
The mathematical sub-discipline of differential equations is foundational in the study of applied mathematics for engineers. Differential equations arise in a variety of contexts, some more theoretical and some of practical interest. The qualitative and quantitative study of differential equations incorporates an elegant mixture of linear algebra and advanced calculus. For this reason, it is expected that the student has already completed courses in (i) linear algebra; (ii) multivariable calculus; and (iii) introductory differential equations.
The course will cover advanced topics of first order and second order ODEs like initial and boundary value problem and stability of solutions and phase portrait of them. A classification will be provided of the various existing types of methods for exploring solutions in connection with the various types of scientific and technological mathematical models that utilize them. The content of the course includes power series techniques as well as the Laplace transformation method for acquiring solutions of ODEs.
Furthermore, PDEs will be studied to model problems involving functions of several variables, and are either solved by hand, or used to create a relevant computer model. PDEs categories will be connected with a wide variety of interesting and important phenomena such as sound, heat, electrostatics, electrodynamics, fluid dynamics, elasticity, or quantum mechanics. All these seemingly distinct physical phenomena can be formalized similarly in terms of PDEs. The content of the course will cover techniques that refer to Elliptic, Parabolic Partial Differential Equations and Hyperbolic Partial Differential Equations as well as Initial and Boundary Conditions. The course will be delivered with lectures that will deliver the necessary theoretical background.
The course will cover advanced topics of first order and second order ODEs like initial and boundary value problem and stability of solutions and phase portrait of them. A classification will be provided of the various existing types of methods for exploring solutions in connection with the various types of scientific and technological mathematical models that utilize them. The content of the course includes power series techniques as well as the Laplace transformation method for acquiring solutions of ODEs.
Furthermore, PDEs will be studied to model problems involving functions of several variables, and are either solved by hand, or used to create a relevant computer model. PDEs categories will be connected with a wide variety of interesting and important phenomena such as sound, heat, electrostatics, electrodynamics, fluid dynamics, elasticity, or quantum mechanics. All these seemingly distinct physical phenomena can be formalized similarly in terms of PDEs. The content of the course will cover techniques that refer to Elliptic, Parabolic Partial Differential Equations and Hyperbolic Partial Differential Equations as well as Initial and Boundary Conditions. The course will be delivered with lectures that will deliver the necessary theoretical background.
The course will facilitate the understanding of research planning and development, while enhancing the PhD student skills for reading, interpreting, writing and presenting his/her scientific and technical ideas to the peer community. The course will also deliver theory and examples of a variety of research methods and ethical principles associated to them.
This course is designed to monitor progress and develop understandings, skills, and outlooks to conduct original, independent research at the PhD level. The student will develop (with the advisor’s guidance) a research plan at the beginning of the semester that will state a research problem/question/hypothesis, its background, outline a research strategy and experimental approach, method of data collection, interpretation and validation, and method of communication of the project results to others. The research plan is used as the basis for assessment of the student’s research progress.
This course develops doctoral students’ ability to read, evaluate, organize, and synthesize current research literature in a critical and methodologically transparent way. By the end of the course, students will be able to formulate a focused review question, design and document an appropriate literature search strategy, critically compare published studies, identify gaps and contradictions in the field of mechanical engineering, and produce a concise survey paper.
Elective Courses
This course introduces students to recently developed and advanced techniques for solving modeling and control problems. The course presents theory and methodology for analysis and modeling of systems and signals, and methods for design and synthesis of feedback controllers.The emphasis of the course will be on mathematical foundations and numerical methods for system modeling from physical properties, identification, andadvanced control of dynamical systems. In particular, it explores state space representation, dynamical modeling from Lagrange equations,model validation, model approximation, Kalman filtering, real-time systemidentification.The course also discovers control techniques such as state-feedback controller, output feedback controller, state observer, stabilizing controllers, automatic tuning, gain scheduling, and auto-calibration.
This course is designed to give a systematic exposition of the central ideas in the design of data structures that are essential in the development of fast algorithms for a variety of applications. The main topics to be covered are:
- Asymptotic notation, function growth, and time-space complexity
- Divide-and-conquer paradigm and recursion
- Basic data structures and their variants
- Heaps and hash tables
- Sorting algorithms and order statistics
- Dynamic programming and its applications
- Graph search algorithms: BFS, DFS, topological sorting
- Shortest path algorithms and network flow problems
- Linear programming and simplex method
- String matching algorithms
- Fundamentals of P/NP problems
This course is designed to familiarize the students with the fundamental topics in digital signal processing and it applications. The course starts from the basics of signals and systems and gradually develops to fundamentals in digital signals processing, random signal processing, and linear optimal filtering.
A tentative list of topics includes:
- Basics of Discrete-Time Signals and Systems
- Discrete-Time Structures
- Digital Filter Design
- Efficient implementation of DFT
- Multirate Signal Processing
- Random Processes & Spectral Estimation
- Introduction to Linear Optimal Filtering
A tentative list of topics includes:
- Basics of Discrete-Time Signals and Systems
- Discrete-Time Structures
- Digital Filter Design
- Efficient implementation of DFT
- Multirate Signal Processing
- Random Processes & Spectral Estimation
- Introduction to Linear Optimal Filtering
This PhD level graduate course consists of three distinct aspects of advanced electronic circuits and systems. The first part focuses on the low frequency aspects of circuits and systems. It aims to equip the students with the fundamentals of the lumped circuit abstraction. Topics covered include: resistive elements and networks; independent and dependent sources; switches and MOS transistors; amplifiers; energy storage elements; dynamics of first- and second-order networks; design in the time and frequency domains; and analog and digital circuits and applications. In the second part of this course, high frequency circuits and components will be covered. This segment of the course covers concepts of transmission line based circuits and antenna for multi-frequency and broadband applications. The targeted applications include consumer electronics and wireless technology. The third and final segment of the course is successful implementation of a project on circuits (analog, high speed or radio frequency) and documentation of a term paper.
This course provides comprehensive knowledge on semiconductor fabrication techniques for VLSI (Very-Large-Scale Integration) applications. Key topics include crystal growth, wafer preparation, epitaxial growth, oxidation processes, and lithography. Students will learn various advanced techniques such as etching, thin-film deposition, diffusion, ion implantation, and metallization. The course also covers critical aspects of testing, assembly, and packaging of semiconductor devices. Students will gain insights into the fabrication steps required for developing high-performance VLSI circuits, with emphasis on addressing modern challenges such as scaling limitations and process control. This course also explores the latest innovations in material and process engineering, which are essential for the continuous advancement of semiconductor technology. This course is designed for PhD students who aspire to pursue careers in semiconductor processing, VLSI design, and related research fields.
Where do our graduates work?
- Career opportunities
- University Faculty Member
- Assistant, Associate, or Research Professor
- Senior Researcher
- Research Scientist
- Electrical Engineer
- Research and Development Engineer
- Power Systems Researcher
- Electronics or Circuit Research Engineer
- Semiconductor or VLSI Researcher
- Signal Processing Researcher
- Telecommunications Researcher
- Machine Learning or Pattern Recognition Researcher
- Control and Automation Researcher
- Biomedical Engineering Researcher
- Optical-Sensor or Photonics Researcher
- Computer Engineering Researcher
- Product Development Engineer
- Research Project Manager
- Technology and Innovation Consultant
- Government Policy or Technical Adviser
- Technology Entrepreneur or Start-up Founder
- Where?
- Universities and higher-education institutions
- National and international research centres
- Power-generation and utility companies
- Renewable-energy and smart-grid organisations
- Electronics and semiconductor industries
- Telecommunications and wireless-technology companies
- Artificial-intelligence and data-technology organisations
- Industrial automation and control companies
- Robotics and intelligent mechatronic systems
- Biomedical and healthcare-technology organisations
- Optical sensing, photonics, and instrumentation
- Computer-engineering and embedded-system companies
- Engineering consulting organisations
- Government ministries and public agencies
- Science, technology, and innovation-policy organisations
- Research-based start-ups and technology ventures
Admissions & Apply now
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Admission
Admission
53 Kabanbay Batyr Ave
Astana city, Republic of Kazakhstan
Astana city, Republic of Kazakhstan