Development of Digital Twin Models for Real-Time Condition Monitoring of Electrical Machines in Electric Vehicle Applications at University of Sheffield 2025

Eligibility

• To apply for the PhD project on Digital Twin Models for Real-Time Condition Monitoring at the University of Sheffield, candidates must be UK home students with a background in Electrical Engineering, electrical machines, or control theory.
• The project is ideal for those interested in fault detection, diagnostics, and machine learning.
• A relevant degree is preferred, but not essential.
• Applicants should also demonstrate a keen interest in the project and are encouraged to contact the supervisor for a pre-application discussion.

Application Process

• Candidates should apply using the information provided on the University of Sheffield website.
• It is recommended to reach out to Dr. Panos Panagiotou, the project supervisor, to discuss your suitability before submitting your application.

Value/Benefits

• This fully funded PhD position covers full UK home tuition fees (£4,786 per year) and provides a UKRI stipend (£19,237 per year) for 3.5 years.
• Additionally, a £1,200 support grant will be provided for project-related expenses, such as travel and conferences.