Leveraging Machine Learning for Design Optimisation of Mechanical Metamaterials

About the Project

Supervisory Team: Professor Jordan Cheer

The main aim of this PhD is to design advanced and novel mechanical metamaterials that can achieve high levels of noise and vibration isolation. This will be achieved through the application of machine learning and artificial intelligence methodologies to enable optimal design of these emerging noise and vibration control treatments.

Mechanical and acoustic metamaterials have been widely demonstrated to offer a lightweight and compact solution to achieving high levels of noise and vibration isolation performance. However, their design can be challenging due in part to their complex structures. In practical applications, this challenge is compounded by additional design constraints related to their size, shape, mass and strength, but also due to their application in environments that introduce uncertainty and variability.

To address this complex challenge, in this PhD project you will explore how machine learning can be utilised to enable the optimal design of mechanical/acoustic metamaterials.

You will develop skills in the application of machine learning for optimal design, as well as in multiphysics modelling, metamaterial design and experimental realisation of these technologies.

The project is part of a larger collaborative research programme, which will offer significant benefits to the successful applicant including

• exposure to real-world engineering challenges motivated by the industry partner
• flexibility to steer the research towards your own strengths and interests
• the opportunity to work as part of a friendly, collaborative and supportive team delivering cutting edge noise and vibration control technologies

Training will be provided in metamaterials, multiphysics modelling, machine learning and experimental testing of metamaterials.

Entry requirements

You must have a UK 2:1 honours degree or its international equivalent.

This PhD studentship is open only to UK applicants.

This project is suitable for applicants with a general interest in:

• structures
• acoustics
• noise and vibration
• control
• digital signal processing
• smart intelligent structures including machine learning and AI

Fees and funding

This project is part of the Royal Academy of Engineering Research Chair in Smart Acoustic Control Technologies, supported by the Royal Academy and BAE Systems.

This project benefits from the support of a large industrial partner and this covers the full cost of UK tuition fees and a significantly enhanced tax free stipend of up to £32,805, which includes the standard UKRI studentship of £21,805 for 26/27 and a £11,000 industrial top-up. The successful applicant will also have access to significant funding to support research activities and training, including attendance at international conferences.

Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.

For more information, please visit our postgraduate research funding pages.

How to apply

Apply now

• programme type: research
• academic year: 2026/27
• if you will be full time or part time
• faculty: Engineering and Physical Sciences
• search for programme PhD Engineering & the Environment (7175)
• please add the name of the supervisor in section 2 of the application.

Applications should include:

• your CV (resumé)
• 2 academic references
• degree transcripts/ certificates to date
• English language qualification (if applicable)