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Data-Centric Engineering, DIgital Twinning Synergy and AI (DACEDITS)

   School of Physics, Engineering and Technology

   Friday, March 31, 2023  Awaiting Funding Decision/Possible External Funding

About the Project

This is part of the new transformative research at University of York which focuses on the world of data-centric engineering, digital twins and AI. This research is transforming the way systems are designed by data and for data. We are synergising our capacity by pairing these two powerful tools to look at complex future systems more realistically.

The DACEDITS research covers both the digital and data technologies to synergise transformation within aerospace, transport, fusion energy, and manufacturing systems' design and control approach, development, and through-life supportability. We are building algorithms to pair data-centric engineering models more optimally with digital twins to achieve enhanced real-time and dynamic insight into complex future systems, including autonomous and connected systems, more/all-electric platforms and network-centric systems. All of our smart solutions are aimed at fostering global efforts to ensure implementation of environmentally-friendly technologies.

Theme 1: Data-Centric Engineering

By leveraging the intersection of engineering and data sciences, we are transforming traditional system design, operation and functional behaviour analytics into optimal cross-sectional analysis of systems for improved robustness and resilience. We are calling it data centricity.

Theme 2: Digital Twinning

Using real-time data and other highly-representative sensory sources, we are enabling learning, reasoning and dynamically recalibrating for improved decision-making. This encompasses the development of cutting-edge digital twin technologies for system performance, design and manufacturing.

Theme 3: AI Optimisation

Improving operational efficiency and achieving swift, accurate, meaningful and highly-effective responses are and will be the defining stratagems of system designers and developers. We are devising AI-optimised algorithms and technologies to realise these stratagems.

Entry requirements:

Candidates should have (or expect to obtain) a minimum of a UK upper second class honours degree (2.1) or equivalent in Engineering, Physics, Computer Science, Mathematics or a closely related subject.

How to apply:

Applicants should apply via the University’s online application system at Please read the application guidance first so that you understand the various steps in the application process.

Funding Notes

This is a self-funded project and you will need to have sufficient funds in place (eg from scholarships, personal funds and/or other sources) to cover the tuition fees and living expenses for the duration of the research degree programme. Please check the School of Physics, Engineering and Technology website View Website for details about funding opportunities at York. You may also email Prof Suresh Perin at for further information.

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