Overview
The PhD program in Mechanical 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 academic, industry and research settings in any of the subfields of the mechanical engineering discipline. The program focuses on the development of an in-depth understanding of the nature, implementation and evaluation of mechanical engineering principles and applications together with the growth of research skills. The current areas of research interest for the PhD in Mechanical Engineering encompass a wide spectrum, with specific focus on priority areas for Kazakhstan, such as: energy engineering, biomedical engineering, advanced design, manufacturing and control, advanced transportation and sustainable 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 mechanical engineering. In addition, program graduates will be prepared for working in 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 mechanical engineering. In addition, program graduates will be prepared for working in 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;
- To prepare future policy and decision-makers for careers in governmental agencies, public service, and the social economy, in Kazakhstan, and globally;
- To prepare entrepreneurs who will be able to promote advanced and innovative science-rich technologies anywhere in the world;
- To prepare new generation of commercially aware and technologically advanced scientists and technologists to lead future developments in the chosen mechanical engineering sub-discipline;
- To prepare future academics and researchers in mechanical 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 emphasis on original and independent researchenabling students to generate new knowledge and make a significant contribution to a specialised area of mechanical engineering.2
- Research aligned with Kazakhstan’s technological prioritiesincluding energy engineering, biomedical engineering, advanced design, manufacturing and control, advanced transportation, and sustainable engineering.3
- Flexible specialisation opportunitiesthrough doctoral-level electives selected according to each student’s research topic and approved by the supervisory committee.4
- Advanced computational and experimental preparationin mathematical modelling, numerical methods, simulation, statistics, engineering design, and research validation.5
- Individual academic supervision by a multidisciplinary committeeincluding a lead supervisor, an internal co-supervisor from NU, and an external co-supervisor from outside the University.6
- Development of teaching and academic experiencethrough participation in the University’s teaching mission as a Graduate Teaching Assistant.7
- International research opportunitiesincluding the possibility of completing a three- to twelve-month research internship at an approved international host institution, subject to funding and programme approval.8
- Strong preparation for publication and scholarly communicationthrough critical literature analysis, conference participation, research presentations, academic writing, and international networking.9
- Training in research leadership, innovation, and entrepreneurship,preparing graduates to lead scientific projects, develop advanced technologies, support policy decisions, and commercialise research outcomes.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 Mechanical Engineering.
- Identify appropriate research topics in their field of study in Mechanical 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 Mechanical Engineering.
- Judge technically and ethically and relate their research to the broader field of knowledge in their Mechanical Engineering sub-discipline.
- Develop their academic/scholarly career through presentations, publications, and national and international networking.
What Will You Learn?
- Advanced applied mathematics and differential equations
- Numerical methods and computational engineering
- Advanced statistics and probability
- Research methodology and research ethics
- Critical analysis of scientific literature
- Research planning, experimental design, and data validation
- Academic writing and scientific communication
- Mathematical modelling and engineering simulation
- Mechanical-system analysis, design, and optimisation
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
DMAE 770 - Digital Transformation Concepts
DMAE 763 - Computational Fluid-Structure Interaction: Methods, Models and Applications
DMAE 753 - Computational and Unsteady Aerodynamics
DMAE 771 - Space Flight Dynamics
DMAE 759 - Space Structures Design
DMAE 756 - Design and Manufacturing with Environmental Concern
DMAE 750 - Advanced Statistics and Probability Theory
DMAE 705 - Sustainable Vehicle Transportation Systems
DMAE 704 - Rocket Propulsion Fundamentals
DMAE 703 - Numerical Techniques for Engineers
DMAE 757 - Design Optimization
DMAE 765 - Advanced Manufacturing Processes and Strategies
DMAE 751 - Modern Control Engineering
DMAE 772 - Advanced Materials and Composites
DMAE 769 – Advanced Computational Fluid Dynamics (CFD) and Heat Transfer in Mechanical Engineering
DMAE 770 - Digital Transformation Concepts
DMAE 763 - Computational Fluid-Structure Interaction: Methods, Models and Applications
DMAE 753 - Computational and Unsteady Aerodynamics
DMAE 771 - Space Flight Dynamics
DMAE 759 - Space Structures Design
DMAE 756 - Design and Manufacturing with Environmental Concern
DMAE 750 - Advanced Statistics and Probability Theory
DMAE 705 - Sustainable Vehicle Transportation Systems
DMAE 704 - Rocket Propulsion Fundamentals
DMAE 703 - Numerical Techniques for Engineers
DMAE 757 - Design Optimization
DMAE 765 - Advanced Manufacturing Processes and Strategies
DMAE 751 - Modern Control Engineering
DMAE 772 - Advanced Materials and Composites
DMAE 769 – Advanced Computational Fluid Dynamics (CFD) and Heat Transfer in Mechanical Engineering
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
Digital transformation of manufacturing industry is essential to gain competitive advantages. This course aims to provide a systematic understanding and knowledge of key concepts and principles for digital transformation and its current practices, tools and processes and future development. The course will also provide hands-on experience using digital transformation tools and methods to enhance product development and enterprises. The course topics include digital tools, methods to support continuous improvements, design for Industry 4.0, enterprise systems, smart product, virtual and augmented reality (VR&AR), digital twin for product development, model based definition/enterprise, lean digital workflow for product development, and digital transformation industrial case studies.
The PhD level course aims to introduce the students to an important and complicated topic in engineering: Fluid Structure interaction (FSI) and its analysis by computational simulation. The students will learn to understand the physics, methods and models available for the study of FSI and how to apply them in engineering applications. Through lectures, seminars and research project work, the course aims to achieve the followings:
1) Understand the fundamental physics and theory of FSI
2) Be Familiar with the numerical methods and models available
3) Be aware of a wide range of FSI phenomena in nature and engineering
4) Know how to use the knowledge and techniques learnt for engineering applications
1) Understand the fundamental physics and theory of FSI
2) Be Familiar with the numerical methods and models available
3) Be aware of a wide range of FSI phenomena in nature and engineering
4) Know how to use the knowledge and techniques learnt for engineering applications
"The course provides deeper knowledge of applied aerodynamics by focusing on computational methods and unsteady flows. During the course, students first review fundamentals of ideal aerodynamics and then extend the scope to include computation of aerodynamic forces for arbitrary streamlined bodies using different panel methods. The course also covers boundary layer corrections to account for viscous drag. Corrections for high speed are also discussed by introducing various compressibility corrections. Unsteady ideal aerodynamics is introduced to examine the effects of sudden plunging, periodic heave and pitching of airfoils. PhD students will be required to develop an advanced numerical model for an applied problem either coupling unsteady aerodynamics with structures or vehicle motion.
This course aims to:
This course aims to:
- Derive governing laws for fundamental of ideal irrotational flows for ideal aerodynamics.
- Apply singularity models to determine the flow fields for simple flows and introduce the concepts of lift generation and circulation.
- Apply steady and unsteady panel methods (source and vortex) for simple geometries to compute the aerodynamic forces for arbitrary streamlined shapes and to compare results with published experimental data to investigate unsteady aerodynamic forces for sudden motion caused by plunging, flapping, or pitching
- Apply boundary layer theory to determine significance of viscous drag forces and predict results for laminar and turbulent flow regimes and investigate benefits of flow control by coding simple interactions of boundary layer flows with mean inviscid flows using Polhausen techniques.
- Apply panel methods to either an aeroelasticity problem or vehicle dynamics problem"
This course is designed to provide PhD students with fundamental knowledge and modeling techniques in the most important fields of space flight dynamics, namely, orbital mechanics, rocket vehicle dynamics, and spacecraft attitude dynamics. The whole course will be delivered through a mathematical software package capable of performing symbolical and numerical calculations. With a strong emphasis on scientific problem-solving using programming, this course equips students with the knowledge and skills necessary to become specialists in the field of space engineering.
This course will immerse students in a Concurrent Engineering Design environment (Machine Design Laboratory), where they will be working on the design of various Space Structures in the context of running research projects in a workshop-project format. Students will become intimately acquainted with bleeding edge space technologies, such as gyroscopic systems, vibration damping systems, satellite structures, composites, honeycombs, truss-cores and nanomaterials. By the end of the course students will be able to perform design of these kinds of space structures. Students will make advanced use of engineering software COMSOL, ANSYS, Mathematica, etc and rapid prototyping facilities provided by Ghalam LLP and the Kazakh Space Agency.
Nowadays it is crucial to be able to design, manufacture and operate systems in a way that they use energy and resources sustainable while at the same time minimize potential negative impact on the environment. Sustainability implies that the use of energy and resources is at a rate that does not compromise the natural environment, or the ability of future generations to meet their own needs. This course addresses fundamental aspects of sustainability in the development of engineering designs and manufacturing. Topics to be presented include: (a) sustainable development; (b) environmental impact of engineering designs; (c) legal aspects associated to mechanical engineering design and environmental impact; (d) Life-Cycle-Analysis (LCA); (e) ISO 14000 Environmental section; (f) integration of recycling in the design; (g) biology-inspired design; and (h) life-cycle cost analysis.
The concepts of probability theory and statistics contribute extensively to the solutions of many types of engineering problems. According to an analysis conducted by LinkedIn, ‘Statistical Analysis and Data Mining’ is one of the most sought-after skills in the job market. Graduates must have a fundamental knowledge of probability theory and statistics to be competitive in the world market. Advanced Statistics and Probability Theory course will best serve graduate students in all engineering disciplines. The main part of this course aims at bringing the students, who arrive with quite varying backgrounds in statistics and probability, up to the same advanced level. The other part discusses advanced topics (e.g. biomedical statistics).
Following the emergence of automotive and other transportation industries as a leading factor in the contribution to the world’s economy, it has also emerged that vehicular transport in general has created complex issues for sustainability in almost every country. The developing countries in particular have experienced a tremendous increase in the use of motorized vehicles in the passenger and transport market, due to their flexible and versatile nature together with a relatively low initial cost. As to how sustainable this explosion of vehicular transport is, is the main focus of this course. Many factors will be drawn together in this course including, innovative technology, basic mechanics, basic chemistry, electricity theory, economics, and public policy. The main concerns due to the increased use of transport energy and sustainability of this increase will be investigated.
A review of current traditional vehicular transport technologies, with emphasis on the energy sources, and especially those of internal combustion engines (petrol and Diesel) and gas turbines will be given.
An exploration of how the traditional technologies could be made more acceptable will be made.
The course will then move on to a review of the increasingly extensive area of newer cleaner transport technologies and vehicular transport systems with a low carbon future in mind, especially the use of hydrogen and batteries as primary energy sources.
The course will also include general economics and health issues associated with transportation systems.
A review of current traditional vehicular transport technologies, with emphasis on the energy sources, and especially those of internal combustion engines (petrol and Diesel) and gas turbines will be given.
An exploration of how the traditional technologies could be made more acceptable will be made.
The course will then move on to a review of the increasingly extensive area of newer cleaner transport technologies and vehicular transport systems with a low carbon future in mind, especially the use of hydrogen and batteries as primary energy sources.
The course will also include general economics and health issues associated with transportation systems.
This course is designed to introduce fundamental aspects of rocket propulsion to graduate students. The course builds on a basic knowledge of thermodynamics, including combustion and gas dynamics, all of which are initially reviewed. This is followed by the basic elements of rocket propulsion, introducing performance parameters and important components of a rocket propulsion system. Different types of propellants will be introduced and discussed, including the important non-chemical propellants. The performance of space flight for several flight regimes, namely atmospheric flight, near-space flight and deep-space flight are analyzed.
This PhD course deals with numerical methods to solve ordinary and partial differential equations of relevance to Mechanical and Aerospace Engineering. Emphasis will be placed on the solution of systems of ordinary differential equations and boundary value problems in partial differential equations using various numerical techniques. The student will be given the opportunity to develop working numerical algorithms on a programming platform (e.g., Mathematica, Matlab, Excel, etc., as indicated by the instructor) to solve a variety of engineering applications. Numerical solutions will be compared with analytical and experimental results when available and students will explore the principles of validity, accuracy and computational efficiency of their numerical solutions.
The course aims to introduce students to the fundamentals of optimization theory. Specifically, the course aims to introduce students to the dynamic field of finding the local and/or global extrema of functions. The students will be able to learn concepts such as unconstrained and constrained optimization, convex and nonconvex optimization, gradient-based, stochastic, and mixed optimization, single shooting, multiple shooting, collocation, differential inclusion methods, homotopy optimization, direct and indirect methods, dynamic programming, linear and quadratic programming problems, etc. After completion of the course, the students will be able to:
The course covers classical optimization formulations & methods, heuristic search methods (simulated annealing, genetic algorithms, particle swarm optimization, and others) and multi-objective optimization along with Pareto optimality.
- Explain the importance of optimization theory in engineering and science.
- Know different methods of solving an optimization problem.
- Understand the necessary and sufficient conditions for optimal solution.
- Formulate and solve constrained and unconstrained optimization problems.
- Interpret the obtained solution and be aware of its shortcomings.
The course covers classical optimization formulations & methods, heuristic search methods (simulated annealing, genetic algorithms, particle swarm optimization, and others) and multi-objective optimization along with Pareto optimality.
This PhD-level graduate course aims to provide deep understanding and fundamental of advanced manufacturing terminology and introduces principles, techniques and applications of abrasive and non-conventional machining processes as well as additive manufacturing. Course topic also includes philosophies, and practices developed by world-class manufacturers to meet current manufacturing challenges, such as lean production, push and pull, just in time, continuous flow manufacturing, kanban, plant-floor quality assurance, warehousing, life cycle assessment and ISO-9000 certification. Theory is integrated with hands-on, computational and laboratory modeling of 3D product using specific processes, including the concepts of failure and improved performance. Students are expected to carry out an independent study by project and term paper on the related topics. In addition, this course will provide an opportunity for the student to study independent relevant manufacturing topics, which are not covered during the lecture.
This course reviews classical control systems and introduces advanced conventional control methods, state space representation, and the design of optimal, adaptive, and robust controllers. It introduces the application of Machine Learning and Artificial Intelligence in Modern Control Engineering. The course also introduces hands-on experience and project-based learning techniques.
The curriculum includes an in-depth discussion on the methods of preparation and characterization techniques of nanomaterials and advanced composites. Additionally, the course will explore the integration of nanomaterials with polymers to enhance properties such as flame retardancy, antistatic conductivity, thermal management, and strain sensing functionalities.
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.
Where do our graduates work?
- Career opportunities
- University Lecturer or Professor
- Senior Researcher
- Research Scientist
- Mechanical Engineering Researcher
- Research and Development Engineer
- Senior Mechanical Engineer
- Energy Engineering Researcher
- Biomedical Engineering Researcher
- Advanced Manufacturing Researcher
- Materials and Nanotechnology Researcher
- Control and Automation Researcher
- Sustainable Transportation Researcher
- Computational or Simulation Researcher
- Engineering Product Developer
- Research Project Manager
- Research Laboratory Director
- Technology and Innovation Consultant
- Government Technical Adviser
- Science and Engineering Policy Adviser
- Technology Entrepreneur or Start-up Founder
- Where?
- Universities and higher-education institutions
- National and international research centres
- Airbus
- Rolls-Royce
- Air Astana
- VietJet
- Alstom
- Air Liquide
- Kazakhstan Paramount Engineering
- Wabtec
- Ghalam
- MCS Egypt, and others.
Admissions & Apply now
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Admission
Admission
53 Kabanbay Batyr Ave
Astana city, Republic of Kazakhstan
Astana city, Republic of Kazakhstan