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). The student will work in world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics, and materials science. PhD project description
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these advanced systems still rely on old technologies based on standard glass lenses and components which are bulky and have limited capabilities. Metamaterials are artificial materials that use digitally-arranged
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these advanced systems still rely on old technologies based on standard glass lenses and components which are bulky and have limited capabilities. Metamaterials are artificial materials that use digitally-arranged
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Fees for 4 years (Full time), £12,000 stipend for 3 years We are pleased to invite applications for a funded PhD studentship exploring how a curated Arts Public Programme can address pressing issues
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for medical applications, micro-robotics, and materials science. PhD project description: The field of medical therapeutics has valuable applications for mobile devices for efficient drug delivery, called micro
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Francesco Fanicchia is a recognised expert in advanced surface engineering and the development of multifunctional protective coatings, specialising in thermal barriers and fire-resistant materials. As a
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world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, bio-printing for medical applications, micro-robotics, and materials science. PhD project
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robotics, and materials science. Project description: 3D-printing of soft robotics is a growing field, with many applications in biomedical devices, electronics, and autonomous machines. Actuators to drive
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This self-funded PhD opportunity focuses on assured multi-domain positioning, navigation, and timing (PNT), integrating data from space-based, terrestrial and platform-based sources of navigation information into versatile benchmarks supporting development of a new generation of assured PNT...
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computational and machine learning approaches to integrate Oxford Nanopore (ONT) long-read data with bulk and single-cell RNA-seq profiles. The aim is to identify host-microbiome molecular signatures that drive