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geometry, and/or data science. Specific topics of focus include, but are not limited to, linear response, random and nonautonomous dynamical systems, spectral analysis, machine learning, data-driven dynamics
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statistical, Bayesian, and deep-learning approaches. Lead improvements in data quality, integration, and reproducibility across multi-centre trials and registries. Collaborate with leading clinicians, engineers
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development. Familiarity with software development lifecycle including design and documentation of software architecture, testing/debugging skills, and version control. Experience applying machine learning
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architecture, testing/debugging skills, and version control. Experience applying machine learning, artificial intelligence, or statistical modelling techniques to digital forensics, online surveillance, or large
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to identify microbial indicators for monitoring marine ecosystems using large-scale short- and long-read sequencing data. You will collaborate with a dynamic team of internal and external researchers to achieve
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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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experience in machine learning research and development, particularly with a specialisation in such areas as: digital forensics, computer vision, biometrics (face or voice recognition, etc.) and natural
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an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed
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to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure
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-sensor hyperspectral data for crop disease detection and monitoring. Develop machine learning or physics-informed models to retrieve reliable spectral and/or biophysical features, from multi-scale