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focuses on scalable, AI-driven decision-making in collaboration with defence industry partners and an academic partner at the University of Melbourne. One role focuses on machine learning for decision
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, algorithmic methods, and machine learning approaches to advance research in melanoma and cancer biology. Specifically, you will support the major project “Predicting Early-Stage Melanoma at High Risk of
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relevant to integration of machine learning and mechanistic models, and development of engines for efficient processing and visualisation of large-scale datasets and system geographic information and
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trials. In this role, you will lead the design, development, and deployment of a real-time clinical AI evaluation platform across Australia, while building your research profile in machine learning with
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genetic variation into elite germplasm. This will require the integration and optimization of several technologies, including genomics, machine learning, genetic simulation, and speed breeding. This is a
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reputed refereed journals and presenting at conferences. Technical expertise in programming (e.g. python) and experience with high-performance computing are highly desirable. Experience in machine learning
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closely with researchers and developers, you will help identify challenges, propose solutions, and improve user interfaces based on feedback and testing. You can learn more about the Australian Internet
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You Completion (level A and B) or near completion (level A) of a PhD in the field of Information Retrieval, Natural Language Processing, or Machine Learning on Textual Data. Demonstrated expert