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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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to assess potato dormancy break, including: data collection, processing, AI model development and classification accuracy assessment. Involved in supporting an electrophysiology-based machine learning model
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machine learning, coupled fire behavior/fire atmosphere modeling, air quality modeling, and system evaluation. Depending on their skills and interests, they can participate in various aspects of the project
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classification accuracy assessment. ii) Involved in supporting an electrophysiology-based machine learning model to predict dormancy break. You will be part of a multidisciplinary academic and industry team
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of microphysiological systems or organ on a chip model for viral agents. Research project emphasis is placed on determining virus growth and stimulation of an appropriate immune response that mimics what is observed in
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approaches will include species distribution models and integration of spatially explicit environmental variables including climate, hurricane disturbance, and land-use, among other global and Caribbean region
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
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effects and their coupled interactions. In effect, this a complex problem that needs the application for AI / machine learning to enable guided, efficient and effective optimization of the CHIPLET
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and Host Area The School of Computing has a strong foundation in computing and information sciences at ANU. We are a transformative centre for research in artificial intelligence and machine learning
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transcriptomic data, that will be integrated with clinical metadata and whole-genome data for developing machine learning models to identify and predict patient factors driving toxicity response and sensitivity