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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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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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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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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
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in writing grant applications and working with machine learning approaches such as MaxEnt, random forest, neural network. Experience using Geographical Information Systems and ecological niche modeling
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processing would be an advantage. Proficiency in statistical software (e.g., R, Python, SAS, or Stata). Experience with clinical informatics approaches (e.g., cluster analysis, machine learning, Bayesian
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enhance our contribution to society. Responsibilities* The successful candidate will work on projects performing analysis of PET neuroimage data, including kinetic modeling and multimodal data synthesis
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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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and machine learning to optimize treatment conditions. Contribute to the development of reproducible stress priming methods and assist in transferring knowledge to agricultural stakeholders. Required
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We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a one-year postdoctoral position. Using recent