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Field
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., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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. when do we stop modelling? How do we track / score the quality of the model What is the required level of quality over time How can quality be brought to the required level Can Machine Learning, Large
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This project offers an exciting opportunity to undertake cutting edge research in electrical machines within the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute
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Machine Learning-based diagnostics and prognostics digital twin system will be developed, aiming to provide fast and reliable predictions of the health of gas turbine engines. Non-confidential operational
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, in addition to interfacing with the established Human-Computer Interaction (HCI) FIT lab. The candidate will be working alongside other researchers on the FLUIDITY project on human-robot interaction
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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
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modelling and simulation techniques and software packages would be an advantage. Programming skills in languages such as Python, C++, MATLAB, are desirable, as is an awareness of machine learning or other AI
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offers an exciting opportunity to undertake cutting edge research in electrical machines within the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute , University
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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