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Field
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Identifying and validating models for complex structures featuring nonlinearity remains a cutting-edge challenge in structural dynamics, with applications spanning civil structures, microelectronics
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willingness to operate and troubleshoot complex instrumentation involving mechanical, electronic and vacuum systems. References: Warr et al., Sci. Adv. 4, eaas9543 (2018) ; Xiao et al., Adv. Mater. 32, 2000063
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applications, facilitating the transition of image-based measurement methods from laboratory research to clinical practice. Digital Image Correlation (DIC) is a well-established, non-contact optical technique
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The Structural Battery Company, a high-tech manufacturer of EV batteries. Building on Cranfield’s previous APC-funded CERABEV successes using epoxy-based systems with intumescent ceramic phases, this project
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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testing) to understand and tailor the physical and chemical interactions within these complex structures. Cranfield University is internationally renowned for its research into materials for extreme
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throughout the water/wastewater value chain, allowing for more informed and robust strategies toward sustainability and circularity. Skills/Experience Required: Process systems engineering, wastewater
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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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for Additive 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
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not sufficiently understood. This involves complex physics at the interface of plasma physics, shock physics, material science and thermodynamics. The objective of this project is the computational