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information. federated learning, whereby a machine learning model can be trained by using data from different clinical sites but without requiring central data aggregation. The data used in this project will
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intensive care data to develop risk prediction models, and translate models into clinical practice. The successful applicant will ideally have a growing research profile in data science, machine learning
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of traits into elite germplasm. This will require the integration of several technologies, such as genomics, machine learning, genetic simulation and speed breeding. This is a unique opportunity for a
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on the application of advanced or specialist or technical research skills or processes, including computer vision, machine learning and data management. Assists in the conduct of complex tasks involving all stages
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Experience in Machine Learning OR human factors, HCI or psychology will be highly regarded. Based at our picturesque and Vibrant St Lucia Campus About UQ As part of the UQ community, you’ll have the
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School of Mathematics and Physics Analytics for the Australian Grains Industry (AAGI) Play a lead role in developing crop trait prediction solutions Utilizes physics-informed machine learning (PIML
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program evaluation Data science methods such as machine learning for structured or unstructured data Qualitative case studies This is a research focused position. Further information can be found by viewing
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models. In-depth understanding of linear algebra and fundamentals of deep learning. Knowledge of Transferability in Machine Learning is desirable. Strong background in multimedia and computer vision tasks
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), and the ability to learn new procedures. High levels of computer proficiency with experience using MS Word, MS Excel, PowerPoint and EndNote. Dedication to subject confidentiality and research ethics
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, co-design workshops, cluster randomized controlled trials (RCTs), implementation science, data linkage, data science, machine learning and artificial intelligence. These are research focused positions