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networks. You should have experience of building machine learning models for environmental applications. A high level of data science and computational expertise is essential, as is experience with Bayesian
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to the project. Job Requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. Min 3 years of relevant experience in computer vision, artificial intelligence, etc
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learning, deep learning and graph neural networks. You should have experience of building machine learning models for environmental applications. A high level of data science and computational expertise is
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at the University of Adelaide, contributing to cutting-edge research in computer vision and machine learning for space applications. This role focuses on advancing machine learning and computer vision research, with
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, or closely related subjects (such as Computer Science, Maths, Engineering or Physics), and possess a strong track record in machine learning, and/or wireless communication, radar sensing. Excellent
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, green finance, ethical supply chains, and behavioural change. Digital and Technologies: AI and machine learning, cybersecurity, spatial intelligence, robotics, human-computer interaction, and digital
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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innovations in computer vision and computer graphics (segmentation, registration, tracking and visualisation) to enable real-time interaction for surgical planning and decision making. The project will provide
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academic record. Demonstrated expertise and leadership in computer vision and machine learning research, including object detection, multi-object tracking, and segmentation. Evidence of leading research
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Computer Science, Applied Mathematics/Statistics, Robotics, Physics, or related discipline, with an excellent academic record. Demonstrated expertise and leadership in computer vision and machine learning research