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) in FPGA design, machine learning or a related field experience in the development of machine learning models using Python and pytorch expertise in two or more of the following technical areas: design
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-based algorithms (e.g., GNNs, deep reinforcement learning) design and simulate dynamic models of megaproject systems prepare and submit journal articles to high-impact publications contribute
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learning at scale. Research directions include designing algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating
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disciplines including aerospace, combustion, design, fluid mechanics, materials, mechanical, mechatronic and robotics engineering. To learn more about the School click here . The Clean Combustion Group