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comprehensive metadata schema is followed, consistent with relevant industry standards (e.g., ISO 19115). 2. Geospatial Analysis and Machine Learning: Develop and implement analytical tools and routines
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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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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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Academic Level B: Completion of a PhD in the field of Computer Science/Artificial Intelligence. Software engineering expertise, including design and implementation of AI-based models (machine learning, deep
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management and machine learning. Our research focuses on how core data systems can enhance AI, and how AI can improve the scalability and intelligence of data infrastructures. We’re looking for a motivated
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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning
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) is seeking a talented academic to join as a Lecturer in Machine learning and Computer Vision. We are looking for a teaching and research academic with a strong expertise in applied AI and current
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clarity, who are able to provide feedback in a timely fashion, and who are interested in developing and applying teaching strategies to support student learning in a range of different settings. Casual
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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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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