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Research Associate: Data driven learning for quality control in Laser Powder Bed Fusion
| Dyddiad hysbysebu: | 24 Ebrill 2025 |
|---|---|
| Oriau: | Llawn Amser |
| Dyddiad cau: | 15 Mai 2025 |
| Lleoliad: | Sheffield, S10 2TN |
| Cwmni: | University of Sheffield |
| Math o swydd: | Dros dro |
| Cyfeirnod swydd: | 1011-43338019 |
Crynodeb
University of Sheffield
An exciting opportunity for a research associate exists within the Additive Manufacturing research group, led by Dr Rob Ward, at the University of Sheffield. You will be part of a programme of research that is fully funded by the Aerospace Technology Institute (ATI) in a large collaborative programme with several Industry partners.
For the aerospace industry and the stringent safety regulations imposed, certification can become a significant barrier to the introduction of new technologies with significant costs and time necessary. Digital transformations to process control and design, including AI, can enable meaningful acceleration of the qualification processes.
Your research will research will incorporate the use of AI neural networks to develop data-driven digital process control methodologies for quality control in the laser powder bed fusion (LPBF) process. Through the analysis of data from in-Situ AM Process Monitoring tools, machine agnostic algorithms will be generated for quality control.
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, watch this short film: www.youtube.com/watch?v=7LblLk18zmo, and follow @sheffielduni and @ShefUniJobs on Twitter for more information.
Apply now by clicking on the Apply button located near the top left of your screen.
An exciting opportunity for a research associate exists within the Additive Manufacturing research group, led by Dr Rob Ward, at the University of Sheffield. You will be part of a programme of research that is fully funded by the Aerospace Technology Institute (ATI) in a large collaborative programme with several Industry partners.
For the aerospace industry and the stringent safety regulations imposed, certification can become a significant barrier to the introduction of new technologies with significant costs and time necessary. Digital transformations to process control and design, including AI, can enable meaningful acceleration of the qualification processes.
Your research will research will incorporate the use of AI neural networks to develop data-driven digital process control methodologies for quality control in the laser powder bed fusion (LPBF) process. Through the analysis of data from in-Situ AM Process Monitoring tools, machine agnostic algorithms will be generated for quality control.
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, watch this short film: www.youtube.com/watch?v=7LblLk18zmo, and follow @sheffielduni and @ShefUniJobs on Twitter for more information.
Apply now by clicking on the Apply button located near the top left of your screen.