FindA University Ltd Featured PhD Programmes
FindA University Ltd Featured PhD Programmes
FindA University Ltd Featured PhD Programmes

Rolls-Royce: Improving the product design process within aerospace and maritime applications using accountable, responsible and transparent AI

Centre for Accountable, Responsible and Transparent AI

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Dr JM Flynn , Dr Neill Campbell No more applications being accepted Competition Funded PhD Project (UK Students Only)

About the Project

Rolls-Royce deploys advanced power generation and propulsion technologies into the aerospace, maritime and defence sectors. The complexity of these systems means that product design, certification and maintenance is driven by rigorous processes, accrued expertise and tacit knowledge. The level of human intuition in this process significantly increases the effort required to develop new products, certify them and minimise the downtime during operation.

Rolls-Royce has many potential use cases for AI in engineering design across a wide range of exciting applications such as the new Future Combat Air System programme, the manufacture of gas turbines and the Artificial Chief Engineer for naval autonomous ships. Opportunities for innovation include improving quality, effectiveness, traceability and accountability in production, service and maintenance.

During your PhD, you will develop new methods to embed decades of domain knowledge into novel product design tools. In doing so, you will be enabling engineers to work more efficiently, make better informed decisions during the design phase, and reduce the likelihood of costly or catastrophic failure during operation. Key research questions could include:

1. How do we convert documented and tacit knowledge into a computer-readable format, compatible with relevant AI methods and tools?
2. How do we discover causal relationships between the design of a component, or system, and available test and in-service data?
3. How do we leverage (1) and (2) to understand and add value to existing data, thereby making engineers more efficient, better informed and capable of performance prediction?
4. How do we achieve assurance for AI-led design decisions in safety-critical products?
5. How do we demonstrate the transparency and intelligibility of AI in order to generate evidence and convince regulators that the technology is safe?

The project will leverage the knowledge within Rolls-Royce Defence IT. You will work with data scientists in Rolls-Royce’s R² Data Labs and with experts within the defence business, who can provide world-leading insight into how the technology will be used in the future. Rolls-Royce also have strong links into the MoD and a range of trade bodies that you could gain exposure to.

Through the unique interdisciplinary approach of the UKRI Centre for Doctoral Training in Accountable, Responsible and Transparent AI, you can demonstrate not only the transformative potential of AI within this field, but also how we will meet the wider challenges and demonstrate to the regulatory authorities that AI technology is both effective and safe to use. Consideration will also be given to policy and procedural advice on how to govern this emerging technology, understanding the cultural and societal impact upon both the engineering community and regulatory authorities while also considering where the technology may need to be adapted to build trust and confidence with the regulators. Further details can be found at:

Applicants should hold, or expect to receive, a First or Upper Second Class Honours degree or equivalent.

Informal enquiries about the project should be directed to Dr Joseph Flynn.

Enquiries about the application process should be sent to [Email Address Removed].

Formal applications should include a research proposal and be made via the University of Bath’s online application form:

Funding Notes

This ART-AI CDT studentship is available on a competition basis for UK students for up to 4 years. Funding will cover Home tuition fees, maintenance at the UKRI minimum doctoral stipend rate (£15,285 per annum in 2020/21, increased annually in line with the GDP deflator), and a training support fee of £1,000 per annum.

We also welcome all-year-round applications from self-funded candidates and candidates who can source their own funding.

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