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Field
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learning algorithms to support research in IDMxS. Key Responsibilites: Apply/ improve/ develop machine learning algorithms to process (e.g., classify, predict) data/ images collected by IDMxS. Help supervise
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models of image processing; (iii) demonstrate experience in academy-industry projects; (iv) interest in publishing high-quality journal papers in the field; (v) demonstrated leadership in research projects
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, Training or work experience in medical imaging, digital image processing, computer vision, pattern recognition, artificial intelligence, machine learning, deep neural networks, and statistics, Hands
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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design, build and maintain a SQL-based relational resource cataloguing research sites, cohorts, biomarkers, imaging facilities, cognitive and digital assessment platforms, and specialist infrastructure
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learning, as well as in digital signal processing and acoustic imaging. The group includes around 20 postdoctoral researchers and PhD research fellows funded by a range of national and international agencies
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Program and will work closely with the staff of the Image Collection and Fieldwork Archives (ICFA) to process the Justin Kerr Collection, which consists of photographs of approximately 6,000 unique
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painted ceramics. The Postdoctoral Fellow in Pre-Columbian Art/Archaeology will receive training in archival processing and digital curation and will support digitization initiatives to increase access
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into prototype systems with practical application potential. Contribute to fabrication process optimization, device prototyping, data interpretation and technical documentation for project milestones and
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to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data