EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering for Manufacturing

This EngD/PhD project at the University of Sheffield, sponsored by Rolls-Royce, offers a unique opportunity to research the application of Generative AI for scalable, sustainable, and trustworthy manufacturing, with a focus on complex aerospace components. The project aims to revolutionize digital inspection processes by reducing reliance on large, labelled datasets, improving defect detection, accelerating model adaptation to new designs, and enhancing trust and explainability in automated decisions.

Traditional machine learning approaches in aerospace manufacturing are limited by the need for extensive annotated data and manual oversight, especially given the rarity and criticality of certain defect types. By leveraging generative AI to create synthetic data, assist annotation, and extract features, this research seeks to dramatically reduce training overhead and lifecycle costs. The project includes an in-depth evaluation of generative AI's capabilities, opportunities, and risks, culminating in a case study on automated defect identification in aerospace components.

Students will benefit from a fully funded four-year scholarship, including tuition fees (for both UK and international students), an annual tax-free stipend of £28,000, and a £35,000 research training support grant for equipment, conferences, travel, and consumables. The program provides access to world-class facilities and expert supervision within the EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering for Manufacturing. Graduates are supported in achieving Chartered Engineer (CEng) status and benefit from strong industry connections, hands-on experience, and tailored training plans.

Applicants should have a first-class or strong 2:1 degree in Mechanical Engineering, Aerospace Engineering, Materials Science, Physics, or Computer Science. Experience with software development, programming (Python, C++/C#), synthetic data generation, and a solid foundation in machine learning and AI are highly desirable. Knowledge of aerospace safety, regulatory requirements, and responsible AI is advantageous. Non-native English speakers must provide evidence of English proficiency (IELTS 6.5 overall, minimum 6.0 in each section or equivalent).

The project is open to both Home (UK) and International students. Applications are submitted via the University of Sheffield admissions system. Candidates should select 'Doctoral Training Course' and 'MADE4 Manufacturing CDT', choosing either EngD or PhD as appropriate. Required documents include transcripts, degree certificates, CV, personal statement, and proof of English language ability if applicable. For further details, visit the application link or contact the program via email.