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group has implemented state-of-the-art deep learning for underwater communications; deep learning models underwater environment based on real data. Our preliminary study shows that state-of-the-art deep
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to frailty assessment could be beneficial. Manual measurements from CT scans, however, are labor-intensive and subject to observer variability. The advent of deep learning in medical imaging presents a
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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview Deep learning has
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deep learning. The purpose of this scholarship is to support a PhD student to contribute to the advancement of infrastructure monitoring technologies with strong industry collaboration. Student type
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curriculum design. A deep understanding of the student learning experience - shaped by high-quality, evidence-based teaching practices - is essential to success in this role. While this is a part-time 0.8FTE
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capable, adaptable, and collaborative researcher with deep expertise in geochemistry, economic geology, or data science, and a strong interest in working across disciplines. The successful applicant will
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exceptional learning and teaching experiences within our Sexology courses that sit within the Discipline of Health Promotion and Sexology. This is a full-time, continuing, permanent opportunity. We are also
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, Security+, CSA+) or equivalent. Extensive experience in ICT security systems, including their design, implementation, and management in academic or research settings. Deep knowledge of cybersecurity
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of mining operations. Digital innovation is playing a key role in this transformation, with developments like automation, predictive analytics, artificial intelligence and machine learning, allowing
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alone. You will be supported by a strong academic leadership team, including the Deputy Head of School, the Dean of Learning and Teaching, and the Faculty Accreditation Team, who will collaborate closely