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quantitative and digital methods, such as descriptive/inferential statistics, data modelling, machine learning (ML), experimental prototyping and technology ideation. A significant degree of autonomy is required
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installation of relevant equipment. Desirable experience therefore includes sheet metal fabrication techniques and the use of machine and hand tools. The role holder should also have the ability to provide
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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developing ideas for application of research outcomes. This post also be linked to research activities linked to the Faculty’s research platforms such as the Power Electronics, Machines and Control Research
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research in areas including Artificial Intelligence, Big Data and Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and their applications in manufacturing
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into hydrogen and nitrogen under practical onboard conditions. Successful candidate will develop and apply computational methods, such as density functional theory based atomistic modelling and machine learning