489 structural-engineering-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" PhD positions in United Kingdom
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Research theme: Chemical Engineering How to apply: uom.link/pgr-apply-2425 UK and EU This 3.5-year PhD project is fully funded by industry. Home and EU students are eligible to apply. International
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, materials science, environmental engineering, or a related field - Strong laboratory skills and an interest in sustainable construction technologies - Experience with cementitious materials, durability
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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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embrittlement, leakage, and long-term material degradation raise critical reliability concerns for flight certification. Structural Health Monitoring (SHM) and Digital Twinning (DT) technologies can address the
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The emergence of 3D concrete printing (3DCP) is reshaping the future of construction, offering unprecedented design freedom, material efficiency, and automation. Unlike conventional concrete casting
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treatment outcomes in vulnerable populations. Training and Student Development: The student will receive interdisciplinary training in: Peptide synthesis and structural analysis Advanced mass spectrometry
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climate change-resilient infrastructure slopes. This PhD project will investigate the impact of different intervention types (e.g. structural measures, modified materials, vegetation, drainage, and/or cover
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modifiers to mitigate this problem, but many of the existing additions have been discovered by chance. To allow more control of structure during the solidification stage as the amount of recycled content is
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structures has become a vital strategy for minimising the environmental and economic costs associated with demolition and new construction. However, one of the most pressing threats to structural integrity is
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exotic crystalline structures that remain poorly understood despite extensive experimental investigations. This project combines cutting-edge sampling techniques with developing machine-learned potentials