Research Fellow

Computing and Engineering
£38,560 - £43,374 per annum
Fixed term for 12 months
37 hours per week

We have an exciting opportunity for a Research Fellow to join the Centre for Thermofluids, Energy Systems, and High-Performance Computing within the Department of Engineering. This world-class centre excels in Digital Twin and Smart Monitoring research, development, and technology innovation.

The School of Computing and Engineering is a research-intensive environment where academics developing tomorrow’s technology teach the next generation of computing and engineering professionals. The School aims to build upon its success in the Research Excellence Framework (REF2021) by investing in its facilities and staff across its broad range of engineering and computing disciplines.

The focus of this role is to support our 'Cyber-physical Systems for Intelligent Monitoring of Operational Composite Structures' project.

In this role, you will be at the forefront of research and development in the field of in-service monitoring, maintenance and prognostics of complex structures and systems, contributing to the integration of cutting-edge technologies in the green energy, infrastructure, aerospace, automotive and marine industry. Your role will entail tackling the technical challenges associated with integrating Machine Learning into structural health monitoring (SHM) of operational engineering structures, accounting for environmental impacts, defect types, and operational uncertainties.

Your responsibilities will encompass the development of SHM systems for rapid, remote actuation, collection and processing of Acoustic Emission (AE) and ultrasonic guided wave (GW) data for rapid, remote and real-time inspections of laboratory-based structures/systems (e.g., Wind Turbine blades) through the utilisation of digital twin technology and will extend to experimenting with established state-of-the-art SHM algorithms and exploring the development of an industry-grade smart SHM system.

You will hold a PhD degree in Structural/Civil, Aerospace, or Mechanical Engineering with significant knowledge and experience in guided wave (GW) and acoustic emission (AE) based SHM of complex engineering structures (composite, metallic, concrete).

Expertise in signal processing, contact acoustic nonlinearity, designing actuator-sensor networks, and machine learning/data clustering/data assimilation is essential. A commitment to conducting high-quality research, publications, and contributing to our strategic ambitions is also required.

The University is deeply committed to equality and diversity for all its students and staff.  We seek to be diverse and inclusive, supporting individuals and groups to fulfil their potential and nurture a sense of belonging.  We strive to be an accessible, inclusive employer, removing barriers for all.  Find out more about our approach to Equality, Diversity and Inclusion, including our commitments and accreditations as a Disability Confident Employer, Stonewall Top 100 Employer, Athena SWAN Bronze Award holder and Race Equality Charter Bronze Award holder.

For further details about this post and to make an application, please select the button shown.

Closing date: 2 July 2024

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