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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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for Machine Learning (AIML) is the largest university‑based machine learning research group in Australia and the country’s first institute dedicated to advancing machine learning, computer vision, deep learning
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candidates in the area of Business Analytics, with particular interest in those applying machine learning and deep learning methods to business domains, such as HR analytics, marketing analytics, and
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with Customer Relationship Management (CRM) or talent management systems. Knowledge, Skills, and Abilities (KSAs) Deep knowledge of experiential learning models, e.g., internships, co?ops, clinical
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learning, and Chinese history and culture. Ideal candidates should possess strong programming skills and solid understanding of AI methodologies, along with a deep engagement with humanistic inquiry and its
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genomic factors associated with increasing age, and vulnerability for neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease and others. For a deep dive into the effects of aging
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engineering or similar. Knowledge and experience with deep learning models applied in computer vision. Remarkable academic trajectory, validated by a strong record of publications in relevant international
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the Job which include, but are not limited to, Computer Vision, Deep Learning, Federated Learning, and Cloud Computing. Desirable: B1 A comprehensive and up-to-date knowledge of current issues and future
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Engineering in the 2025 QS World University Rankings by Subjects. The EEE Rapid-Rich Object SEarch (ROSE) Lab focuses on research in: (i) visual search & retrieval, (ii) video analytics & deep learning, and
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, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities