Job Description

Job Title:

Research Associate: ROSEHIPS Programme Grant

Posting Start Date:

17/11/2025

Job Id:

1901

School/Department:

Mechanical, Aerospace & Civil Engineering

Work Arrangement:

Full Time (Hybrid)

Contract Type:

Fixed-term

Salary per annum ():

38,784.00 - 47,389.00

Closing Date:

14/12/2025
The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world-class university.



We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more.

Overview

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 focussed 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.

Main duties and responsibilities

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.

Person Specification

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.

Criteria

Essential or desirable

Stage(s) assessed at

Have a good honours degree in an engineering discipline, computer science or mathematics (or equivalent experience).


Essential


Application


Have a PhD or be close to completion (or have equivalent experience) in computer science, engineering, mathematics or a relevant discipline.

Essential


Application


Knowledge and experience relevant to the project aims including population-based SHM and associated structural dynamics.


Essential


Interview


Have experience/expertise in transfer learning for SHM data; preferably, kernel-based, neural network and Bayesian.


Essential


Interview


Experience and track record in code writing for engineering problems in e.g. Matlab, python, FORTRAN, C/C++ (or equivalents).

Essential


Interview


Specific expertise in experiment design and testing of structures across environmental conditions.

Essential


Interview


Effective communication skills, both written and verbal, experience of delivering research presentations, writing research papers and attending conferences and meetings.

Essential


Interview


Ability to work effectively within a research group and in collaboration with a range of external partners.

Essential


Interview


Ability to analyse and solve problems and produce results for research publication.


Essential


Interview


Ability to organise own research work and meet deadlines for required deliverables.


Essential


Interview


Experience of adapting own skills to new circumstances.


Desirable


Interview

Further Information

Grade

7

Salary

38,784 - 47,389

Work arrangement

Full-time

Duration

16 months starting 1 February 2026

Line manager

Principal Investigator

Direct reports

Principal Investigator

Our website

https://www.sheffield.ac.uk/mac


For informal enquiries about this job contactProfessor Keith Worden, Principal Investigator: on k.worden@sheffield.ac.uk

Next steps in the recruitment process

It is anticipated that the selection process will take place in January. This will consist of Interview and Presentation. We plan to let candidates know if they have progressed to the selection stage on the week commencing 12th January 2026. If you need any support, equipment or adjustments to enable you to participate in any element of the recruitment process you can contact mac-recruitment@sheffield.ac.uk

Our vision and strategic plan

We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision ().

What we offer

A minimum of 41days annual leave including bank holiday and closure days (pro rata) with the ability to purchase more. Flexible working opportunities, including hybrid working for some roles. Generous pension scheme. A wide range of discounts and rewards on shopping, eating out and travel. A variety of staff networks, providing opportunities for social interaction, peer support and personal development (for example, Race Equality, LGBT+, Women's and Parent's networks). Recognition Awards to reward staff who go above and beyond in their role. A commitment to your development access to learning and mentoring schemes; integrated with our Academic Career Pathways. A range of generous family-friendly policies + paid time off for parenting and caring emergencies
+ support for those going through the menopause
+ paid time off and support for fertility treatment
+ and more





We are a Disability Confident Employer. If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.


We are a research university with a global reputation for excellence. Our ideas and expertise change the world for the better, making a real difference to society. We know that when people come together with different views, approaches and insights it can lead to richer, more creative and innovative teaching and research and the highest levels of student experience. Our University Vision (www.sheffield.ac.uk/vision) outlines our commitment to building a diverse community of staff and students that recognises and values the abilities, backgrounds, beliefs and ways of living for everyone.