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Field
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Extended reality (XR) is steadily developing into a reliable digital environment, bringing tangible advantages to various practical scenarios. Realistic use cases include immersive medical training
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Manufacturing research group (CfAM) at the University of Nottingham. The student will work in world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, soft
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Manufacturing research group (CfAM). The student will work in world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics, and
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/ . About the role Project Background: The Institute of Health Informatics is looking to recruit a full time PhD studentship to join our welcoming and vibrant Institute. The main purpose of this studentship
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the transition to a full-time training model, and how these demands can be best managed to maximise adaptations and performance, and mitigate injury risk. The successful candidate will audit the current scientific
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investigate strategies to enhance communication security, focusing on resilience against jamming and spoofing attacks. Students will work on designing secure architectures that ensure data integrity and system
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The Department of Psychology are offering seven funded, part-time PhD training posts. You should hold a 1st Class honours degree, or be working towards a 1st Class degree (or equivalent). The posts
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involve the development of new data, techniques, and evaluations. The successful candidate will also take part in dissemination of research findings. The student will work as part of the interdisciplinary
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factors (learning curve). These will be linked with the CCTA imaging biomarker data (quantitative plaque analysis) that is being collected as part of the EU HORIZON TARGET study to determine personalised
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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