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Field
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are in particular targeting development of data-driven high-performance computing techniques for unbiased discovery of generative models & theory and algorithms for network inference with special reference
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requirements: Presentation of the academic qualifications and/or diplomas, if applicable. Enrolment in Master’s in Informatics Engineering. Work plan: The work consists of the development and implementation
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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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. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims
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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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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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working collaboratively to lead the world to better health. Here, you will thrive in an innovative and inclusive atmosphere and your personal development and wellbeing will be supported. We invite you to
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disease patients using radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical
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radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical imaging. Within our research
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modelling, and the economics of mental health Support economic analysis of healthcare utilisation, outcomes and costs using national datasets Develop and apply algorithms for cost-effectiveness analysis