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3.5-year D.Phil. studentship Project: Computational Fracture Mechanics Supervisors: Prof Emilio Martínez-Pañeda Oxford’s Mechanics of Materials Lab is seeking a PhD (DPhil) student to support the
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interactions into account with data-driven method. This research is inherently multidisciplinary, lying at the interface of fluid and solid mechanics, acoustics, and computing science. It will potentially
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PhD Studentship: Subcortical brain development and disorders, funded PhD at the University of Exeter
Decoding the precise programme regulating neurodevelopment has been crucial to our understanding of brain disorders. A central question is how the brain generates its remarkable diversity of cell
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requirements A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, and manufacturing) with a minimum 60% mark in
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supervision from a leading expert in Rolls-Royce throughout the project. How to Apply: All applications should be made online . Under Campus, please select ‘Loughborough’ and select Programme ‘Mechanical and
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k Si3N4 and then the additive manufacturing of the components with the aim of achieving complex geometries with the enhanced ceramic. Funding notes: This PhD programme will be hosted in the School
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. Requirements: The candidate will have a 1st class undergraduate or Master’s degree (or equivalent) in Applied Mathematics, Physics, Aerospace Engineering, Mechanical Engineering, Computer Science, or a related
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PhD studentship in Mechanical: Bioprinted 3D In Vitro Cardiac Models Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional
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are disease-specific, reflect shared mechanisms, or capture distinct clinical phenotypes. This project will investigate whether small non-coding RNAs can provide disease-specific signatures for DLB, and whether
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project