The post holder will be located in Central Cambridge Cambridgeshire, UK.
A position exists for a Research Assistant/Associate in the Department of Engineering to develop numerical modelling methods using machine learning and other methods such as optimisation for materials "made to design". The project will involve a close collaboration with in-house experimental activities as well as international groups developing new methods to assemble micro-architected materials with designed properties. These methods include additive manufacture and self-assembly and the project will involve developing modelling methodologies for understanding the generation of defects during manufacture and proposing solutions to circumvent these defects.
The specific goals include:
- Development of numerical methods (including but not exclusively graph neural networks) for understanding the generation of defects during additive manufacturing processes such as micro stereolithography.
- Developing optimisation methods that include the effect of these defects.
- Validation of methods against experimental data.
The skills, qualifications and experience required to perform the role will include a good working knowledge of Finite Element computations with a strong continuum mechanics background and experience in machine learning methods. The applicant will have obtained or be close to obtaining a PhD in Mechanics of Materials/Mechanical Engineering/Materials or related subjects.
Research Assistant: £27,116 - £31,406
Research Associate: £33,309 - £40,927
Fixed-term: The funds for this post are available for 24 months in the first instance.
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If you have any questions about this vacancy or the application process, please contact: Hilde Hambro, Group Administrator, email email@example.com (Tel +01223 748 243).
Please quote reference NM30956 on your application and in any correspondence about this vacancy.
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