165 structures-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" PhD positions in United Kingdom
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structures, demonstrating the ability to engineer the membrane shape. They will test the effect of using their structures in selected devices. The student will be trained in wet lab techniques and advanced
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insole architectures to redistribute plantar pressure and improve comfort. To support continuous monitoring, sensing elements will be incorporated within the insole structure to capture changes that may
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and Environmental Sustainability Environmental Impact of Construction on Peatlands Exploring the mechanisms of wave propagation in granular materials Effects of bio-inspired remediation techniques
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characterised at atomic resolution via crystal structures of PrfA–peptide complexes. Building on these findings, this PhD will develop peptide-based PrfA inhibitors as novel anti-Listeria agents. The project will
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library of polymer candidates with varied physicochemical properties (charge, size, structure, biodegradability) Formulate polymer–mRNA nanoparticles and characterise their size, stability, and mucus
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for the UK offshore wind sector, as set out in the Offshore Wind Industrial Growth Plan. The manufacturing process involves the infusion of resin into a mould to form a composite structure with glass or
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microwave and laser fields to probe their energy structure, or to carefully tailored magnetic fields to reveal their behaviour due to gravity. Aided by laser-cooled beryllium ions and laser cooling of the
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group with structured training and strong technical support. 2. Candidate profile This project is ideal for candidates from Mechanical, Electrical, Biomedical, Materials Engineering, or related
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mitigate climate impacts while benefiting both society and the environment. This research will explore how robotics are applied in sectors such as construction, manufacturing, and defence, and assess how
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temporal structure and missing data affect multimodal learning Identifying fundamental trade-offs between accuracy, efficiency, and robustness. The project emphasises foundational machine learning research