however, still in its infancy.

The data-driven, highly-structured nature of MBSE aligns exactly with the requirements and ethos of the current AI revolution. Despite a lack of attention to-date, it is a prime candidate to leverage the benefits of automation, generation, and efficiency that AI has proven in many domains. The aim is to move beyond the current state-of-the-art of systems engineering: “the application of systems thinking to the realisation of stakeholder needs, when developing engineered products and services” by introducing modern, and future, digital technologies for the rapid development and evaluation of novel and innovative system architectures.

The ultimate ambition is to develop artificial intelligence (AI) tools and code that can be utilised in MBSE to provide underpinning capability to improve efficiency and productivity throughout the design and development of complex products. As such, this project will offer the prospect student a unique opportunity to be at the forefront of AI-based systems engineering. The EngD student will:

• Conduct a state-of-the-art (SOTA) overview of current AI methods, tools and algorithmic approaches, identifying where they offer the most value within engineering workflows.
• Based on the SOTA, identify gaps and opportunities for MBSE approaches and tools.
• Utilise 3D models that incorporate AI to accelerate discovery, development and demonstration of novel system architectures.
• Implement novel ideas in realistic Systems Engineering scenarios at NCC, HVMC and other national initiatives focussing on tools, techniques and practices to improve efficiency, quality and value.
• Demonstrate the benefits of MBSE in early product lifecycle, such as; defining requirements, planning and assessment, concept development and system architecture exploration.
• Investigate implementation of MBSE in verification, validation and uncertainty analysis/quantification by generating evidence to provide traceability, confidence and supporting evidence for product certification and compliance.
• Be based primarily at NCC and interact directly and closely with the appropriate technical staff and experts. It is likely that the main context of the project will move within a composite-based research space, supporting a priority high-value sector such as aerospace/space, however, a focus on broader topics is also possible.

Eligibility: Home/permanent UK residents subject to security clearance

however, still in its infancy.

The data-driven, highly-structured nature of MBSE aligns exactly with the requirements and ethos of the current AI revolution. Despite a lack of attention to-date, it is a prime candidate to leverage the benefits of automation, generation, and efficiency that AI has proven in many domains. The aim is to move beyond the current state-of-the-art of systems engineering: “the application of systems thinking to the realisation of stakeholder needs, when developing engineered products and services” by introducing modern, and future, digital technologies for the rapid development and evaluation of novel and innovative system architectures.

The ultimate ambition is to develop artificial intelligence (AI) tools and code that can be utilised in MBSE to provide underpinning capability to improve efficiency and productivity throughout the design and development of complex products. As such, this project will offer the prospect student a unique opportunity to be at the forefront of AI-based systems engineering. The EngD student will:

• Conduct a state-of-the-art (SOTA) overview of current AI methods, tools and algorithmic approaches, identifying where they offer the most value within engineering workflows.
• Based on the SOTA, identify gaps and opportunities for MBSE approaches and tools.
• Utilise 3D models that incorporate AI to accelerate discovery, development and demonstration of novel system architectures.
• Implement novel ideas in realistic Systems Engineering scenarios at NCC, HVMC and other national initiatives focussing on tools, techniques and practices to improve efficiency, quality and value.
• Demonstrate the benefits of MBSE in early product lifecycle, such as; defining requirements, planning and assessment, concept development and system architecture exploration.
• Investigate implementation of MBSE in verification, validation and uncertainty analysis/quantification by generating evidence to provide traceability, confidence and supporting evidence for product certification and compliance.
• Be based primarily at NCC and interact directly and closely with the appropriate technical staff and experts. It is likely that the main context of the project will move within a composite-based research space, supporting a priority high-value sector such as aerospace/space, however, a focus on broader topics is also possible.

Eligibility: Home/permanent UK residents subject to security clearance