37 parallel-computing-numerical-methods PhD positions at Cranfield University in United-States
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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Applicants should have a first or second class UK honours degree or equivalent in in Design, Engineering, Computer Science/IT or a related subject. Experience in system design, and/or manufacturing is
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to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development
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requirements A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, and manufacturing) with a minimum 60% mark in
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms,...
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised