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and Community Trust for a Just and Effective Net Zero Transition , a two-year, multi-region, mixed-method study focused on the role of trust in Australia's decarbonisation efforts. The project
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Australian National University | Canberra, Australian Capital Territory | Australia | about 20 hours ago
at the John Curtin School of Medical Research (JCSMR), within the ANU College of Science and Medicine. This role will lead the development of advanced deep learning frameworks—including graph neural networks
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this international network, tasked with establishing and building capability to support the Australian and international SKA science communities, thereby ushering in the next era of astronomical discovery and advanced
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in CFD software tools such as Ansys Fluent and CFX and with experience in coding using MATLAB, Python, and User-Defined Functions (UDFs). Strong technical communication skills. At Level B
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, you will: Support survey instrument design, testing and implementation Undertake data collection, cleaning, coding and analysis, including comparative analysis Assist with communicating results to a
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the Critical Minerals Trailblazer JCU have secured funding to undertake a high-profile research project “EarthBank: An Australian geochemistry network activity enabling the analysis, preservation and
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experience in python, C++ or other relevant language and experience in deep neural networks Strong mathematical capability, especially for Theme 1, with applicants holding an undergraduate or postgraduate
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Australian National University | Canberra, Australian Capital Territory | Australia | about 20 hours ago
international networks and by world-class facilities. To find out more about the Science at ANU community, follow us on social media at Instagram and Facebook For further information please contact, Professor
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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong
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. The project, "Building the bridge from GWAS to Breeder through multi-omic network data fusion", focuses on transforming GWAS discoveries into actionable breeding insights. Using sorghum as a model, the work