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-polymer materials. These biomimetic hybrid scaffolds will form controlled double-network hydrogels in which the mechanical and biocompatibility properties of the scaffold can be orthogonally tuned through
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engineering, computational neuroscience, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from
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Women in Engineering Day. We are also Disability Confident Level 1 Employers and members of the Business Disability Forum and Stonewall University Champions Programme. Cranfield Doctoral Network Research
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The University of Exeter’s Department of Computer Science is inviting applications for a PhD studentship funded by Faculty of Environmental Science. For eligible students, the studentship will cover
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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in the study of problems in quantum many-body physics through the lens of quantum information and quantum computing? Do you enjoy studying complex quantum mechanical systems both from a physical and a
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Deadline: 30 September 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing
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processing, or optimisation to turn heterogeneous knowledge (channel/network state, maps and topology, mobility, hardware constraints, and task-level KPIs) into reliable and efficient decisions. The work spans
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providing world-class professional development and networking opportunities that strengthen both research outcomes and student success. The Engineering and Mathematics group is part of the School
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an implementation support package Project Supervisors: Dr Sam McLean Prof Beth Fylan Dr Justine Tomlinson Jaspreet Sohal Project Description: This is a fully funded training programme to conduct research