Qualification Type: | PhD |
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Location: | Cranfield |
Funding for: | UK Students |
Funding amount: | Stipend of £25,222 (tax-free) per year for four years |
Hours: | Full Time |
Placed On: | 3rd July 2025 |
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Closes: | 31st July 2025 |
Reference: | SATM597 |
Overview:
As data becomes more accessible, new challenges arise around how best to use it—especially in complex, multi-system environments like aerospace. Ontologies offer a powerful solution by providing a structured, semantic framework that enhances knowledge sharing and data reuse across different platforms and systems.
Project Aim
This PhD will develop an ontology-based methodology to improve interoperability across complex assets and systems. The research will explore how common data architectures can be used to enhance semantic understanding and enable better decision-making across system-of-systems environments—such as fleets with multiple aircraft types.
Objectives
The project will use tools such as SHACL (Shapes Constraint Language), the NCT3TA reference model, and standards like HISO 100xx and ISO/IEC 11179-xx. Prior experience with these tools is not required—training will be provided.
Industrial Sponsorship
The PhD is fully funded through the EPSRC ICASE scheme and supported by BAE Systems, offering strong industrial relevance and collaboration. The student will be based at Cranfield University in the Centre for Digital and Design Engineering, part of the Manufacturing, Materials and Design theme. The Centre provides access to advanced simulation, visualisation, and high-performance computing facilities, supporting applied research in digital engineering.
Throughout the project, there will be regular collaboration with BAE Systems, including site visits and access to real industrial use cases. Additional engagement with other organisations may also be part of the research journey, providing exposure to a broad network of practitioners and stakeholders.
Funding and Eligibility
Candidate Requirements
We welcome applicants with a First or Upper Second Class honours degree (or equivalent) in engineering, software development, or another quantitative-focused discipline. Ideal candidates will be analytical, self-motivated, and interested in working across both technical and applied industrial domains.
Key Details
How to Apply:
To apply for this PhD opportunity, please view full details on our website, and complete the application form via the ‘Apply’ button above.
For further information please contact John Erkoyuncu
Email: j.a.erkoyuncu@cranfield.ac.uk
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