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Description of thesis topic Turbulence in magnetic fields, or magnetohydrodynamic turbulence, is a fundamental process that underpins our understanding of a variety of natural and industrial
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of continual learning and Natural Language Processing (NLP) to automate the cyber-attack attribution process . - Establish solutions for automatic identification of attacker-oriented countermeasures
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model of complex systems, considering both cyber and physical aspects, and the human element. Use techniques like Attack Trees and Bayesian Attack Trees to predict attack stages and identify compromised
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way to overcome the limit of theoretical methods and measurement technologies to acquire the needed fine-scale data to investigate the fundamental physics. The project will build on the Mathematical
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adversaries might exploit quantum technology. In this project, you will conduct an in-depth threat analysis of quantum-computer attacks on cyber-physical systems, considering system configurations, data
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within the food supply chain. When grown in co-culture with methanogens, the conversion process would result in the production of biogas (methane and carbon dioxide). Research aim and objectives Previous
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searching for a highly motivated candidate with the following qualifications: Background in relevant engineering, mathematics, physics or computer sciences is highly desirable. Proficiency in at least one of
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community committed to excellent research with impact. This project forms an exciting research opportunity to join Manchester Met’s AI, Digital and Cyber-Physical Systems theme for improving life quality
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of Engineering and Physical Sciences, next page select “PhD Elect & Elect Eng (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Hywel Morgan Applications should
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experience in cyber security/risk management and knowledge of cyber-physical systems are highly desirable. In-depth knowledge of regulatory frameworks and standards in cyber security, such as NIST standards