Research Associate in Predictive Modelling in Complex Uncertain Environments

University of Sheffield - Department of Mechanical Engineering

Are you interested in working for a world top 100 University?

We have an exciting opportunity in the Department of Mechanical Engineering to work on the development of hybrid models for structural dynamics, with the ultimate aim of improving the current techniques used to assess the condition and safety of offshore and aerospace structures.

The Research Associate will take a leading role in the development of the hybrid models proposed. This will include implementing physics-based modelling of structural dynamics and incorporating machine learning techniques into the predictors.

We are looking for an outstanding person with an interest and expertise in machine learning, structural health monitoring, and structural dynamics. The successful candidate will work in one of the world’s best and largest structural dynamics research groups. The researcher will be supported and actively encouraged to attend conferences and publish in high quality peer-reviewed journals. You will have, or be about to obtain, a PhD in engineering, mathematics, computer science, or a related discipline.

We’re one of the best not-for-profit organisations to work for in the UK. The University’s Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and professional development.

We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching, and student experience.

To find out what makes the University of Sheffield a remarkable place to work, follow @sheffielduni and @ShefUniJobs on Twitter for more information.

Closing date 27 June 2018.

Fixed-term until 24 June 2021.

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Northern England