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) improve the estimation method using information from the first part of the work and additional constraints, including a Machine Learning approach. (3) inspect how the mismatched expected and measured
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subsystems • High performance tunable and reconfigurable oscillators and frequency synthesisers • Application of AI / Machine Learning to physical layer circuitry, signals and waveforms Researchers can expect
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various applications. Potential applications include environmental monitoring, process manufacturing, machining, scientific characterisation, and renewable energy systems. The outcomes of this research will
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The Centre for Doctoral Training in Machining, Assembly and Digital Engineering for Manufacturing (MADE4Manufacturing CDT) is a collaboration between the Faculty of Engineering, Advanced
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themes of “digital research”. The research elements of the post will include the application of big data approaches, artificial intelligence and machine learning to neurodegenerative disease drug design or
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of wear and fatigue failures – design life is 20 years but bearings rarely last that long (3). As machines have got larger, this state has worsened. Manufacturing very large bearings (up to 5m diameter) is
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experience, or keen to learn the research knowledge in power systems, cyber-physical systems, computer science, information and communications technologies, and computing and data platforms. The perspective
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Modelling, DEM simulations and Machine Learning Approaches. You will have access to the excellent training opportunities at the University of Sheffield. A range of highly desirable skills will be learnt
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and monitoring data can be used to develop machine agnostic process control methodologies. Perform metallographic and non-destructive assessment of LPBF builds to assess and classify build quality
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artificial intelligence/machine learning may be applied are encouraged to apply. If you are interested in research in brain-machine interfaces, and are unsure about whether you have the right background