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more sensitive and faster cancer imaging. This PhD project will focus on surface functionalisation of metascintillators to optimise their scintillation performance, light yield, timing resolution, and
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of Computational Solid Dynamics Building upon very recent work made by the supervisory team, this FULLY FUNDED 4-year PhD project will investigate challenging aspects such as: (1) exploration of a truly “n” multi
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) Applications are invited for a three-year PhD studentship. The studentship will start on1st Jan, 2026. Project Description Glioblastoma (GBM) is the most aggressive and treatment-resistant form of brain cancer
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Loughborough University Vice Chancellor’s PhD Cluster – Super-Smart Textiles (SuS-Tex) for Healthcare and Sports. The Doctoral Researcher will join a cohort of five researchers belonging to the SuS-Tex cluster
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PhD Project: Advanced 3D/4D-Printing of Responsive Biomaterial Devices Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre
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PhD Project: 3D-Printed Drug Delivery “Microbots” for Personalised Healthcare Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing
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Project details: Iron is crucial for athlete health and performance, yet iron deficiency is a common diagnosis in active populations. Iron deficiency can hinder haematological adaptations and reduce the body’s capacity for oxygen transport. Additionally, iron plays a vital role in energy...
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Ovarian cancer is the deadliest of all gynaecological cancers (>2000 deaths/year, UK). It is described as a silent killer as most diagnoses occur after it has spread to the peritoneal cavity (metastasis). It is known that peritoneal cells contribute to the growth of metastatic tumours....
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, process stability, and the downstream consolidation and performance of remanufactured composites. This fully-funded PhD project fits within a wider research programme with industrial partners and an
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available