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machine learning frameworks such as recurrent neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection
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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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Net Zero 2050 goals, electric motors must undergo a transformational leap—from today’s typical power densities of 2–5 kW/kg to a step-change 10–25 kW/kg by 2035. The highest power dense motors today
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to the commencement of the PhD. Vision We are seeking for a highly motivated PhD student to conduct cutting edge research of the AI techniques that will power future flexible manufacturing systems. Together, we will