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Tao Yang

Professor at University of Nottingham

University of Nottingham

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United Kingdom

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Research Interests

Aerospace Engineering

10%

Avionics

20%

Microgrid Technology

20%

Electrical Engineering

20%

Resonant Converters

20%

Rf Circuit

10%

Dynamic Systems

10%

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Positions1

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Tao Yang

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University of Nottingham

PhD Studentship - Digital-twin Technology to Accelerate Development of Electric Propulsion Systems

This PhD studentship at the University of Nottingham offers an exciting opportunity to join the Power Electronics, Machine and Control (PEMC) research group within the Faculty of Engineering. The PEMC group is renowned for its cutting-edge research in digital twin technology, particularly as it applies to accelerating the development of electric propulsion systems for aviation. With over 150 members, including 18 academics and approximately 120 PhD students and postdoctoral fellows, the group provides a vibrant and collaborative research environment. Facilities include 2500m 2 of research space and capabilities for construction and testing up to 5MW, supporting advanced experimental work. The project is closely linked to the EU-funded €40M NEWBORN initiative, which focuses on next-generation high-power fuel cells for airborne applications. The aim is to develop a real-time Multiphysics Digital Twin for electric propulsion hardware, thereby accelerating future electric propulsion system development. The transition to net-zero aviation is a critical global objective, as aviation currently accounts for 2–3% of global CO₂ emissions. Electric propulsion systems, from hybrid-electric to fully electric architectures, are seen as transformative solutions for reducing greenhouse gas emissions, offering benefits such as lower emissions, reduced noise, and improved energy efficiency. As a PhD researcher, you will undertake tasks including reviewing real-time digital twin technology, developing skills in simulation platforms such as Typhoon and SpeedGoat, and creating a real-time digital twin—either physical or AI-based—of electric propulsion systems. This includes modeling propulsion motors, power converters, fuel cells, and batteries within the simulation platform. You will also train the digital twin using real-time data from available hardware and conduct electrical power level studies to identify optimal solutions for distributed electric propulsion. Applicants should be enthusiastic and self-motivated, with a first-class degree in electrical engineering, control engineering, or computer science, and strong electrical engineering knowledge. The studentship is open to both UK and international candidates. Funding details are not specified; candidates are encouraged to contact Professor Tao Yang for further information regarding funding support. To apply, email Professor Tao Yang at [email protected] to discuss your interest and eligibility. Applications are open until filled, with a formal deadline of 10 May 2026. For more information, visit the project webpage: https://www.nottingham.ac.uk/engineering/pg-research/phd-projects/digital-twin-technology.aspx .

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