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Research Fellow in Earth System modelling Job No.: 682250 Location: Clayton campus Employment Type: Full-time Duration: 3-year fixed-term appointment Remuneration: $83,280 - $113,025 pa Level A
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available for passionate and early career Researcher to join our team within the College of Science and Engineering as a Postdoctoral Research Fellow, Geophysical Ore Body Modelling. Full-time; fixed-term
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methodologies and contribute to a new data product that integrates model outputs into our platform - helping us better understand environmental exposures and health outcomes. About This Opportunity This is a
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focus on financial incentives designed to promote safer and lower carbon driving. In this role, you will contribute to the estimation and extrapolation of treatment effects from trial data, modelling
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computer vision models for real-world impact. Full-time appointment on a fixed term basis for two years. Base salary range: Level C, $144,143 – $165,809 p.a. (pro-rata) plus 17% superannuation. About the
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Drive cutting-edge AI research in traffic video analytics, developing and deploying state-of-the-art computer vision models for real-world impact. Full-time appointment on a fixed term basis for two
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(written and verbal), ability to collaborate effectively. If you would like to be part of an impactful cutting‑edge research project focused on solving pressing challenges of modeling temporal dynamics in
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
, attention-based models, and multi-modal learning approaches—to model RNA-mediated regulatory mechanisms and their dynamic interactions in disease. The position is part of an NHMRC Ideas Grant project
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floating photovoltaics sector. The role also involves contributing to the design and execution of research projects, including quantitative and qualitative analyses, modelling FPV integration with existing
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position within a Research Infrastructure? No Offer Description Drive cutting-edge AI research in traffic video analytics, developing and deploying state-of-the-art computer vision models for real-world