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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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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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-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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develop an understanding of real-world challenges in oral health and healthcare. The role will report to Professor Ali Darendeliler . The Lecturer will make significant contribution to teaching and learning
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for teaching, learning, and the student experience. This includes institution-wide initiatives such as curriculum quality and sustainability, enhancing student engagement, assessment reform and AI, learning
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for a collaborative, strategic leader with: A deep understanding of contemporary business education and operational acumen. Experience in online learning and digital education innovation. Strong
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or advanced skills and competencies have deep and broad experience in effective clinical teaching and learning, as evidenced by high-quality student outcomes demonstrated excellence in clinical activities