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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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computer vision algorithms to detect clinical interventions performed by nurses and situations of agitation and risk of falling. Volume of data available for the project: Video capture in a hospital
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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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on the littoral environment. Algorithm development includes photogrammetric measurements of wave parameters, image stabilization, and use of AI/ML models for image segmentation and classification. Algorithms will
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development team Interacting with Continental business areas Developing and integrating AI algorithms into the real development progress Preparing academic publications such as patent applications and research
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at the John Curtin School of Medical Research (JCSMR), within the ANU College of Science and Medicine. This role will lead the development of advanced deep learning frameworks—including graph neural networks
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, optimization techniques, and optimal energy management algorithm development for the optimal operation of the system and applications. • Strong knowledge of power electronics, wide band gap semiconductor
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web technologies Experience in teaching bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms
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, inferential, and multivariate methods, including principal component analysis (PCA), regression, and machine learning algorithms (e.g., Random Forest), with the aim of integrating various environmental exposure
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy