Research Associate in Data-driven Modelling

1 month ago


Sheffield, United Kingdom University of Sheffield Full time

Applications are invited for a Research Associate position in Data Driven Modelling and Implementation for Smart Manufacturing. The role will contribute to the metrology informatics activities of the EPSRC Future Metrology Spoke at the University of Sheffield. This short-term position is available for immediate start and ends on 30 August 2024.

The revolution in smart manufacturing is being driven by digitalisation and data analytics. The need for smart analytics algorithms that can support human and machine decision-making is fundamental to this progression. The Future Metrology Hub team at Sheffield have been developing analytics algorithms using a mixture of machine learning and Bayesian methods for the monitoring of robotics based manufacturing processes. The role will contribute to this effort further in expanding our capabilities to challenging data analytics problems.

You will have a PhD in Computer Science, Control Engineering, Statistics or a related discipline, or have equivalent research experience. You will also have expertise in data-driven modelling, machine learning, statistics or other relevant disciplines. Combined with a strong analytical skills, having experience of developing Python or MATLAB implementations of modelling and machine learning algorithms is essential for this role.

The successful applicant will join a team of researchers and contribute to the development of novel analytics algorithms and their implementation culminating in the building of a demonstrator system. They will experience a vibrant and collaborative research environment offered by a large multi-disciplinary research project.

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.



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