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complex, multi-model ecological forecasting workflow. The fellow will gain valuable experience in advanced model development, calibration, and synthesis of the forest succession, fire severity, and climate
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to contribute to cutting-edge research that could revolutionise bushfire management? We are seeking Postdoctoral Research Fellow to join a team of researchers on an ARC Linkage Project titled, ‘Forecasting live
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of three topics: 1. Combining synthetic aperture radar (SAR) images with probabilistic weather prediction models to view and predict dynamic sea ice properties. 2. Using multi-frequency SAR, coupled with in
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-performance computing, machine learning models (eg. LLM), probabilistic models for data, novel techniques for making measurements, visualization tools, and community-oriented foundational software tools. Please
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successful appointee will be centrally involved in the delivery of the ARIA-funded Forecasting Tipping Points programme , and will work collaboratively with Professor Doug Benn (University of St Andrews) and
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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Forecasting system developed by CSIRO. Along with a $42,000 p.a. scholarship for three and a half years, the student will have the opportunity to undertake a funded 60-day industry placement with one of our
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in real-world public health applications, including pandemic preparedness, outbreak forecasting, and integrating diverse data sources to inform decision-making. PREFERRED QUALIFICATIONS: PhD in
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(e.g. a transferable ML for flexibility forecasting) with a focus on designing a robust and scalable ML tool that can be deployed across our various pilot sites in the EU and the UK. The Research Fellow
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predictions. To mitigate these effects, advanced ML techniques such as Bayesian deep learning, probabilistic models, and uncertainty quantification methods can be applied to enhance model robustness