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data (e.g. DFT, MP2) and experimental data into AI-driven pipelines for structure–property learning and reactivity prediction. Applying AI models to real-world problems in virtual screening, ligand
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using Large Language Models (LLM) to query and reason geospatial data. The project aims to develop a pilot decision support systems in collaboration with industry partners. The Postdoctoral Research
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Australian National University | Canberra, Australian Capital Territory | Australia | about 11 hours ago
-cell RNA-sequencing data, with a focus on mouse models of age-related macular degeneration. The successful candidate will join Associate Professor Jean Wen’s research group, conducting independent
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Models (LLM) to query and reason geospatial data. The project aims to develop a pilot decision support systems in collaboration with industry partners. The Postdoctoral Research Fellow will undertake
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data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python), including a sound understanding of FAIR data principles, data management and
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(Academic Level A) Visa sponsorship may be available for this position Based at our St Lucia Campus - Brisbane About This Opportunity If you are passionate about computational modelling, thrive on solving
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Technology (SET) This position plays a vital role in developing advanced theoretical tools and models for superconducting quantum materials research, contributing to leading-edge defence-related technologies
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. Working closely with the ABI program’s leadership team, you’ll contribute to data curation, protocol development, predictive modelling, and novel analytics for large-scale neurocritical care datasets. As
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engineering. About the opportunity Play a key role in advancing the AuScope Geochemistry platform ‘EarthBank’ at UWA. Contributing to new and existing analytical datasets and data models, improving
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engineering. About the opportunity Play a key role in advancing the AuScope Geochemistry platform ‘EarthBank’ at UWA. Contributing to new and existing analytical datasets and data models, improving