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Field
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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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of causal reasoning tools, including causal inference, counterfactual analysis, causal discovery. Development of deep learning methods on computer vision. Job Requirements: Preferably PhD in Computer
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novel research methodologies in computer vision, deep learning architectures, and neuro-fuzzy systems to contribute to the development of robust AI frameworks for medical diagnosis and treatment support
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/research/about-us/ AIML is the largest University based computer vision and machine learning research group in Australia, with over two hundred members including academics, engineers, research staff and
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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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through their work. Preferred Skills: Experience with single-cell analysis and microbial culturing techniques. Familiarity with Machine-Learning and computational tools and programming languages such as
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health monitoring, preferably with a publication record in top-tier journals; and (c) be proficient in mainstream research frameworks for deep learning and computer vision. Applicants are invited
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the largest computer vision and machine learning research group in Australia with over 180 members including academics, research staff and students. The AIML works on a mixture of fundamental and
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factors. Though not required, we are particularly interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and
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related context, Robotics and autonomous systems, Computer vision, Embedded and Realtime Systems Knowledge in promoting group activities and Business development Experience of processing of data and