Application of Deep Learning methods for breakthrough noise and vibration control using metamaterials (Trinity College Dublin)

Closing Date
28 May 2021

Research Topic

 Environmental challenges are one of the main drivers of technological evolution. Sustainable development of society is only possible in the presence of an enduring effort to reduce the environmental signature of human activities. In this context noise mitigation will be one of the major challenges of the next decades and noise scenarios will change dramatically in terms of absolute levels and frequency content. Acoustic metamaterials (AMs) offer the potential for radical changes in our approach to noise and vibration control. These materials are non-intuitive and achieve properties previously considered impossible in natural materials. Traditional or human centered approaches to design are incapable of achieving optimal solutions in the vast design spaces offered by AMs.

This research intends to overcome these challenges by developing Deep Learning methods for optimized, low-cost design tools. The application of these tools to the latest additive manufacturing technologies aims to achieve designs that, until recently, would have been considered unmanufacturable. High fidelity numerical modelling tools will be used to develop a training dataset suitable for deep learning networks. This dataset will include the topological features required to achieve the frequency bandgaps where sound wave propagation is prohibited. From the trained networks, optimized and highly accurate acoustic metamaterials will be produced without the need for further high cost modelling.

This research will use the Additive Research lab within the SFI AMBER facility to realise the designed materials and to quantify the precision of their manufacture. Following acoustic testing the experimental findings will be compared with theoretical and numerical results. The impact of the manufacturing will be assessed to identify issues which lead to degraded performance of the acoustic metamaterial. This information will then be included in a second training phase of the deep learning networks allowing the networks to produce designs which have been optimized for practical manufacture.


 This role is funded through the Provost’s PhD Project Award. The funding covers the fees (EU/non- EU) plus a €17,316 p/a stipend for a PhD student to work on the project.

Details on this PhD studentship are available at:

What will the student gain?

 At Trinity, the PhD student will be given the opportunity to work with and learn from global leaders in research, to benefit from their experience and networks. As the only Irish member of the prestigious League of 22 European Research Universities (LERU), Trinity is committed to providing excellence in education and research. We meet the highest standards in learning, innovation and independent critical enquiry, and we win more than 50% of the European Research funding coming into Ireland.

How long is the programme?

 Our doctoral candidates are registered on the 4 year structured Trinity PhD programme. The student will have access to a variety of taught modules, both discipline specific and generic skills, to enhance and support their own research. We welcome the best students each year to begin their PhD journey with us here in Dublin.

The Selection Process in Trinity

 Applications will be acknowledged by email. If you do not receive confirmation of receipt within 3 working days of submitting your application, please contact Dr Kennedy prior to the closing date/time.

The Selection Committee (Interview Panel) may include members of the Academic and Administrative community together with External Assessor(s) who are expert in the area. Given the degree of co-ordination and planning to have a Selection Committee available on the specified date, the University regrets that it may not be in a position to offer alternate selection dates. Where candidates are unavailable, reserves may be drawn from a shortlist. Outcomes of interviews are notified in writing to candidates and are issued no later than 5 working days following the selection day.

The interview will take place via video conferencing. The selection process will consist of a presentation and interview.

Application Procedure

 Applicants should submit a cover letter and full curriculum vitae (including the names and contact details of two referees) by Friday 28th of May 2021 to

Dr. John Kennedy

Interviews will be arranged, and the selection process completed by mid-June.

Interested? Apply here.

Posted on 26th March 2021 in Job Opportunities in Acoustics