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of robotic equipment within bespoke cells to improve the efficiency and performance of machines. Provide guidance, assistance and technical advice with programming and integration of associated software and
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validating data, spinning up virtual machines for research groups and enabling access to the relevant data as appropriate, providing support for researchers using the environment and dealing with any data
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supports the semi-automated checking of research outputs, including machine learning and Artificial Intelligence models. Working closely with the Research and Innovation Platforms Team, you will oversee
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/interview) A degree (Bachelor’s, Master’s, or PhD or equivalent experience) in Software Engineering, Computer Networks, Embedded Systems, AI, Data Engineering, or a related subject (assessed at: application
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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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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