83 structural-engineering "https:" "https:" "https:" "https:" "https:" "https:" "Dip" positions at University of Bristol in United Kingdom
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We are seeking to hire a Research Associate on a project to design and develop biomaterials for cartilage growth plate engineering. We are seeking a world-class research scientist with a high degree
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supports people to achieve their potential, please see our staff blog: https://engineering.blogs.bristol.ac.uk/category/engineering-includes-me/ Contract type: Open ended Work pattern: Full time Grade: H
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of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog: https://engineering.blogs.bristol.ac.uk/category/engineering-includes-me/ Contract type: Fixed term for 12
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like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog: https://engineering.blogs.bristol.ac.uk/category/engineering
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commitment to high-quality teaching and the ability to develop and deliver engaging education in materials engineering and structural performance are required. We particularly welcome candidates with a
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work packages. To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog: https
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supports people to achieve their potential, please see our staff blog: https://engineering.blogs.bristol.ac.uk/category/engineering-includes-me/ Contract type: Open ended with fixed funding until 31/03/2028
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, please see our staff blog: https://engineering.blogs.bristol.ac.uk/category/engineering-includes-me/ Contract type: Open ended Work pattern: Full time Grade: L / M Salary: Grade L £59,966 - £ 67,468 per
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like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog: https://engineering.blogs.bristol.ac.uk/category/engineering
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Project description Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to