Location: | Sheffield |
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Salary: | £37,999 to £46,485 per annum. Grade 7 |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 27th November 2024 |
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Closes: | 6th December 2024 |
Job Ref: | UOS042313 |
Contract Type: Fixed-term with a start date of 3 February 2025, and a fixed end date of 31 Jan 2026.
Faculty: Faculty of Engineering
Location: Mappin Building
We are pleased to announce an exciting new opportunity to advance the state-of-the-art in digitalisation of manufacturing processes. This project will involve utilising various sensing techniques to capture the process data, followed by processing, fusion and analytics of sensor data to identify links between the process parameters and the resulting product characteristics. This will also involve sensor-supported precision assembly for large aerostructures, especially landing gear, to enhance operator safety, efficiency, and productivity through automation and advanced techniques.
The University of Sheffield is seeking to appoint a talented and highly motivated Research Associate in digitalisation of manufacturing processes. The position is associated with funding from two projects: an EPSRC project: Intelligent engineering coatings for in-manufacture and in-service monitoring of critical safety products COATIN (EP/T024607/1) and the ATI project LANDone on Sensor-supported precision assembly for large aerostructures, especially landing gear, to enhance operator safety, efficiency, and productivity through automation and advanced techniques. You will join a world-class team of digital manufacturing researchers, with frequent opportunities to engage in networking and development activities with other researchers across the consortium and progress your career as a future research leader.
As part of the COATIN project, you will develop in-process monitoring techniques that utilises a variety of sensing technologies to generate data that will be used to measure and monitor manufacturing process parameters. You will develop an approach that combines data processing, fusion and analytics to identify links between process data obtained from sensors and the production outcomes. Also, develop a control method that can make use of the sensor data and the identified links to ensure successful production outcomes. As part of the LANDone project you will work on sensor-supported precision assembly for large aerostructures, to enhance operator safety, efficiency, and productivity through automation and advanced techniques.
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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