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criticality, and attack likelihood. You will develop a systematic method to identify at-risk system assets, creating a crypto inventory for analysis. Using techniques like Attack Trees, you will predict
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and tailored cybersecurity measures. You will join the Cyber Security Research Group recognised as Academic Centre of Excellence for Cyber Security Research (ACE-CSR) and Education (ACE-CSE), and work
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PhD Studentship: Centre for Doctoral Training in Composite Materials, Sustainability and Manufacture
. The occurrence of defects is a complex problem involving many factors. A combination of statistical tools and advanced machine learning techniques will be used to help develop mitigation strategies to avoid over
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it depends critically on the acceptation of the proposed experimental session by the “selection committee” of the EMFL consortium. The PhD student will develop the physical model on nonlinear
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the performance of UK WWTPs, which will require water utilities to assess technologies and practices for future micropollutants consents. This project aims to understand and develop technologies that can act as a
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addition to rehabilitation, which has long been employed as method to enhance recovery from clinical stress events, there is burgeoning clinical and research interest in prehabilitation, an approach employed to prepare