Research Associate: ROSEHIPS Programme Grant

Research Associate – Dynamics Research Group

The Dynamics Research Group in the Department of Mechanical Engineering is seeking to appoint a Research Associate with excellent research skills as part of the EPSRC-funded  ROSEHIPS  Programme Grant. The ROSEHIPS project is focused on creating new technology for Population-Based Structural Health Monitoring (PBSHM). It is a consortium between the Universities of Sheffield, Cambridge, Exeter and Queen's University Belfast and a large group of industrial partners.

The research work will focus on developing transfer learning technology for PBSHM. Specifically, both kernel-based and neural network methods will be used to transfer diagnostic capability between structures in a population. Bayesian approaches will also be emphasised.

The Research Associate will take a leading role in a specific programme of research focussing on the development of transfer learning for PBSHM. The programme will also involve validation of the methods on populations of laboratory structures in the Laboratory for Validation and Verification. Experiments will be carried out across different environments.

• Apply mathematical and numerical modelling tools in order to develop transfer learning methods and apply them to population-based SHM applications.
• Develop kernel-based and neural-network-based technologies for transfer learning and mullti-task learning for the analysis of vibration-based features from structures.
• Experimentally validate the resulting novel methodologies for engineering use cases defined in the ROSEHIPS project. In this case, the focus is on model bridge structures.
• Proactively collaborate with other members of the team, both in Sheffield and more widely, to ensure that the research results have the maximum benefit, including short visits to partners and other forms of interaction.
• Produce high-quality written journal and conference papers of the research results, including, relevant literature surveys, graphs, mathematical analysis, and written text.
• Effectively manage your workload in order to accomplish project goals and tasks on time and to a high standard, including selecting appropriate scientific approaches, and conducting yourself with scientific rigor and integrity.
• Take a leading role in developing new ideas and assist others around to help contribute to the idea generation process.
• Participate in and contribute to all ROSEHIPS project events, including communication of your research results at project meetings and more widely at conferences and outreach events.
• Plan for specific aspects of the research project and contribute to research project planning both locally and more widely across the consortium, ensuring that you have an ongoing plan for your own work, incorporating issues such as the availability of resources, deadlines, project milestones and overall research aims.
• Further develop your research skills, including leadership, communication and other transferable skills.
• You will make a full and active contribution to the principles of the ‘Sheffield Academic’. These include the achievement of excellence in applied teaching and research, and scholarly pursuits to make a genuine difference in the subject area and to the University’s achievements as a whole.
• As a member of staff you will be encouraged to make ethical decisions in your role, embedding the University sustainability strategy into your working activities wherever possible.
• Carry out other duties, commensurate with the grade and remit of the post.

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role’s criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.

• Have a good honours degree in an engineering discipline, computer science or mathematics (or equivalent experience).
• Have a PhD or be close to completion (or…