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computer vision and machine learning research group in Australia, with over two hundred members including academics, engineers, research staff and students. AIML works on a mixture of fundamental and
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/) infrastructure uses a variety of methods such as density functional theory, graph neural networks, computer vision, classical force field, and natural language processing. We are currently focusing on
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, Embedded Systems, Cloud/Green/Ubiquitous/Mobile Computing and Networking, Cybersecurity and Trusted Computing, Machine Learning, Data-Centric Computing, Computer Architecture •Power Electronics
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include natural language processing ( NLP ), natural language understanding ( NLU ), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition ( ASR
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Summary The research laboratory is seeking a motivated undergraduate student to assist with ongoing research projects in machine learning, deep learning, computer vision, and related areas. The
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Challenge grant. The successful candidate will work closely with the Principal Investigators (PIs) to develop and implement innovative research integrating machine learning, computer vision, and
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in areas such as Neural network vulnerabilities and defenses, Anomaly detection, Adversarial machine learning, Computer vision, and Autonomous Robots is desired. The successful applicant will work on
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inference), and automated machine learning. holding (or close to acquiring) a PhD degree in Computer Science, Artificial Intelligence or a closely related field; strong research vision and an academic
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. Strong expertise in machine learning and deep learning, with demonstrated experience in one or more of the following areas: computer vision, markerless pose estimation, movement analysis, behavioural
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experience in Civil Engineering, Geomatics, Computer Science, Data Science, or a related field Experience with machine learning, data analytics, or computer vision techniques Programming experience in Python