Leveraging Machine Learning for Design Optimisation of Mechanical Metamaterials

About the Project

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/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 operation in changing 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.

For informal enquiries please get in touch with the Professor Jordan Cheer –

To discuss aspects related to the CISDnS CDT please contact the directorate –

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 and smart intelligent structures including machine learning and AI.

CISDnS is committed to promoting equality, diversity and inclusivity. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break or are transitioning into a new role. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance.

Funding: Full-time studentships will cover UK tuition fees and an enhanced tax-free stipend of up to £27,700 per year for 4 years along with a substantial budget for research, travel, and centre activities.

How To Apply: Search for a Postgraduate Programme of Study (soton.ac.uk).

Select Full-time or Part-time, programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences, next page select “Integrated PhD in Complex Integrated Systems for Defence and Security (2025-26)”

In Section 2 of the application form you should insert the name of the supervisor Professor Jordan Cheer

To help us track our recruitment effort, please indicate in your email – cover/motivation letter where (jobs-near-me.eu) you saw this job posting.

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