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Field
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches
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) their undergraduate degree in physics, engineering or chemistry (preferably with first class honours or equivalent) and we expect the PhD candidate to develop the expertise required to lead an experimental research
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of differential materials within them. The goal of this project will be to develop responsive 4D-printed biomaterial devices for drug delivery or regenerative medicine. The student will formulate new 3D-printable
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mechanisms, with the current generation having significant drawbacks, including low energy efficiency, high operating voltage or temperature. This project will develop the materials, methods, and designs
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into their structure. However, we don’t yet know how to design these complex printed parts and we are still developing new leading-edge materials to grant them new capabilities. Advantages: In this PhD studentship, you
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that rotations play in gas-surface collisions. Working within a well-supported and experienced research group, the student will join and further develop a unique Magnetic Molecular Interferometer (MMI) apparatus
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define observable events based on expert knowledge and available evidence. Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
Location: West Cambridge, Cambridgeshire A position exists, for a Research Assistant/Associate in Photonics Integration of Graphene and Related Materials. The aim is to develop a new class of
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases