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& Health is a national leader in learning, teaching and research, with close affiliations to several of Australia’s finest hospitals, research institutes and health care organisations. The Discipline of
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/AI expertise) systems Engineering or Control Systems (with applications to large-scale projects) artificial Intelligence / Machine Learning (with interest in applications to megaprojects or governance
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
. The project is aimed to improve our in-house developed process-based computer model and use it to represent the soil ecohydrological and biogeochemical interactions across various carbon and nitrogen soil pools
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: developing and testing new approaches to water resources modelling, application of Bayesian inference methods to environmental problems, machine learning and data science applications, undertaking analysis and
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computational tools for analyzing immunogenomics data in the context of gastrointestinal autoimmune diseases and Type 1 Diabetes. Lead the application of AI and machine learning to identify novel therapeutic
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to help monitor and combat online social influence and promote a healthy information environment. The successful candidate will join the School of Computing and Mathematical Sciences as part of a project
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disciplines including aerospace, combustion, design, fluid mechanics, materials, mechanical, mechatronic and robotics engineering. To learn more about the School click here . The Clean Combustion Group
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) Country Australia Application Deadline 6 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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redox conditions, salinity, weathering conditions and/or biological productivity. The successful candidate will preferably have experience in aspects of isotopic geochemistry applied to sedimentary
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of scientific monitoring programs demonstrated experience managing and integrating large datasets experience working in large teams and organising complex field programs a strong commitment to delivering outcomes