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Field
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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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need, with direct routes to translation and impact. You’ll have access to world-class computational facilities, real-world datasets, expert supervision across engineering and clinical science, and the
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methodologies for human-centric generative design, validated through case studies in sectors like engineering design, smart manufacturing, and supply chain management, etc. Develop open-source tools
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. Electroencephalography (EEG) has emerged as a non-invasive and economical alternative technique for studying neurological disorders. However, current approaches rely primarily on single-channel or pairwise connectivity
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Project details: Surface features are important in additively manufactured parts. While additive manufacturing technology has made great strides in the realisation of complex shapes, topologies and
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, economic viability, and robustness to realistic operational uncertainty. PhD (or equivalent) in control engineering or closely related discipline. Track record in at least two areas: model predictive control
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will have or expect at least a II(i) Undergraduate honours degree or Masters degree (or equivalent) in Materials Science, Chemical Engineering, Chemistry, Physics or related discipline. A background in
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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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of your current level of study, academic background, any relevant experience and your motivation to study this PhD project. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a