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skills (Python preferred) and solid understanding of machine learning and deep learning, including computer vision techniques. Ability to read, write, and communicate scientific texts clearly; strong
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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these systems are responsibly integrated into our daily lives requires a deep understanding of their operational mechanisms and societal impacts. Doctoral students of the centre will engage in
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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engineering applications. What you will gain Advanced training in cutting-edge characterisation techniques. Deep expertise in materials science and microstructural analysis. Collaboration with Cummins
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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: The research project aims to identify the most effective machine learning/deep learning models for modelling normal IoT device behaviour and detecting anomalies in encrypted traffic patterns. Furthermore, it is
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, integrating genetic, clinical, and demographic data for national research and trials. Establish high-fidelity MUC1 sequencing using long-range PCR and ultra-deep nanopore sequencing to resolve the complex VNTR
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Scale Physics group led by Prof. Peter Liljeroth. The group consists currently of 3 Academy Research Fellows, 1 Postdoctoral Researcher and 5 Doctoral Researchers. The group focuses studying physical