Research Focus
- The cross-application of computational hydrodynamics (CFD) and data-driven modelling studies how to optimize and predict the behaviour of complex physical systems through scientific machine learning and generating artificial intelligence (Generative AI).
- Dynamic systems theory and machine learning to develop new modelling methods and control algorithms to accelerate the optimization of scientific computing and engineering systems.
- Modelling and control of complex systems, in particular how to apply a data-driven approach to deal with and analyse large-scale dynamic systems in areas such as aviation, energy and engineering.
- Machine learning is combined with hydrodynamics, smart optimization algorithms and the depth of control of the polyphysical system, exploring the applications of automation and intelligent systems in the industrial and scientific fields.
Programme Structure and Funding
The project is a full-time Ph.D. project and is taught in 4-5 years (48-60 months). Only 1 recruits.
Suitable Academic Backgrounds
Mechanical engineering, aerospace engineering, electronic engineering, engineering mechanics, computing fluids, applied mathematics, computer science, control engineering, energy and power engineering
Entry Requirements
- Academic background: master’s degree in mechanical or electronic engineering and enthusiasm for scientific machine learning, computational modelling, and advanced artificial intelligence of physical systems
- Performance requirements: GPA 3.7
- Language requirements: TOEFL: 88; or IELTS: 6.5; Exempted national B.A./Master degree in English
- Recommendation: Provide 2 an academic recommendation
Preferred qualifications
Candidates with research experience are more favoured.
Application Materials
- Personal statements;
- Curricula vitae (including detailed information on the history of education, employment and internships, as well as any relevant research experience);
- 2An academic letter of recommendation;
- Previous reports and diplomas;
- GRE/GMAT Performance Report (not required);
- Financial records (3 months, with a clear indication of the name of the account holder and the amount of funds available in United States dollars);
- Copy of passport identity information page.
Application Period
Deadline for applying for admission in spring:8Month15Deadline for application for school day fall:12Month15Day
Application Process
Up to 11 months for applicants to submit their English curriculum vitae and related materials, we will conduct an initial assessment 12 months through which potential mentors will be invited to interview 1 months 15 days, and will be required to formally present applications 2-3 months through a web-based web site for shortlisted candidates to be interviewed by the College Admission Board for 4 months for admission notices: above is the time point of the fall admission process.
Tuition and Living Costs
Living costs
Approximately US$ 25,706/year (depending on individual circumstances).
- Tuition fees: 2025-26 school year, 64,400/year (Note: Tuition fees increase slightly per year).
Career Prospects
The Rensler Institute of Technology (RPI) has a deep research tradition in the field of aerospace and mechanical engineering, and its doctoral graduates are well known for their solid theoretical credentials and their strong ability to solve complex engineering problems. Graduates are generally highly competitive in academia, high-end industrial research and development and in core national research institutions.
The overall pay level is attractive, and in the United States, entry rates for Ph.D. graduates into industry generally range from 110,000 to 160,000 dollars, depending on the industry and region; entry to academia or national laboratories is subject to a different remuneration system, usually with relatively low entry rates but well-being and stable career paths. - Aerospace and national defence: core research and development of aircraft design, propulsion systems, structural dynamics, aerodynamics and advanced manufacturing processes in institutions where graduates can enter aerospace giants such as Lockheed Martin, Boeing, Nosrop Gruman or NASA.
-
Advanced manufacturing and robotics: In the areas of automation, material enrichment (3D printing) and intelligent robots, graduates are the research and development backbone, serving a wide range of areas, from high-end equipment manufacturers to technology companies, to promote industrial 4.0 change. - Energy and power systems: in research and development focusing on turbine machinery, renewable energy systems, propulsion technology and thermal management systems, the employment orientation includes the power companies, energy equipment manufacturers and the motor sector of automobiles/aviation enterprises.
-
(c) Micro-computer electricity systems (MEMS), nanotechnology and advanced materials: interdisciplinary research to provide innovative solutions for semiconductors, sensors and the next generation of miniaturization equipment. - Academia and national studies: Some of the doctoral graduates have chosen to teach at universities or to join national laboratories such as Agong, Oak Ridge and others, to conduct basic, forward-looking scientific research and to prepare future engineers.
