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research program advancing carbon-neutral energy systems modelling for Australia's energy transition. This role focuses on the development and application of advanced forecasting and scenario analysis
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data science methods to build explainable and integrated machine learning models that can be utilised by health services to make real-time, data-informed clinical decisions in youth mental health care
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, neurobiological or computational modelling frameworks. Your key responsibilities will involve: Original Research: Conduct original research in the areas of functional and structural neuroimaging, with a focus on
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how control parameters (e.g. bucket speed, size, depth, and packing density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design
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, stem cell models, and nanotechnology, within a collaborative and innovative research environment. It is an exciting opportunity to be at the forefront of translational cancer research. Key
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) in FPGA design, machine learning or a related field experience in the development of machine learning models using Python and pytorch expertise in two or more of the following technical areas: design
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-based algorithms (e.g., GNNs, deep reinforcement learning) design and simulate dynamic models of megaproject systems prepare and submit journal articles to high-impact publications contribute
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manufacturers and the ability to meet milestones and deadlines good analytical skills and attention to detail and ability to utilise data analytics and modelling software accordingly. Sponsorship / work rights
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" . The research will further span cutting-edge imaging technologies, single-cell sequencing, metabolomics, proteomics and experimental models ranging from human neurons to mouse and non-human primates. You will be