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Field
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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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-leading database of MRI images of childhood tumours and have developed AI approaches to diagnose different types of tumour. To be useful for patients, this needs to be delivered in hospitals in real time
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that provides AI-based suggestions. The work will consist in the improvement and evolution of previously developed models, as well as interacting with project partners to integrate algorithms and conduct field
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borehole electromagnetic data during drilling. This includes the further development and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed
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. The goal is to contribute broadly to research on applications of AI in medicine, and in particular to the development and validation of novel computational language models, algorithms, and tools
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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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, Natural Language Processing, and structured knowledge representations. As a researcher within Integreat, you will contribute to developing next-generation Machine Learning for advanced data analysis
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, Natural Language Processing, and structured knowledge representations. As a researcher within Integreat, you will contribute to developing next-generation Machine Learning for advanced data analysis
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description participate in developing the theoretical framework and research tools participate in designing the data
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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