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28 Aug 2025 Job Information Organisation/Company UNIVERSITY OF SYDNEY Research Field Computer science Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country Australia
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
Pacific. We strongly encourage applications from these groups. The University actively encourages applications from Aboriginal and Torres Strait Islander people. For more information on employment
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experience in machine and/or deep learning applied to geospatial data. Demonstrated experience in the use of HPC and handling of very large datasets. Experience in software development and contribution
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and data integration, with the ability to connect structured data sources to large language models. In addition, you will have exceptional communication and relationship management skills that enable
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., atmospheric correction), spectral unmixing, and variable retrieval, feature extraction. Experience working with cloud-based platforms and large-scale EO data workflows. Strong programming skills with experience
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Associate to undertake fundamental and applied research into novel deep learning approaches to analysing LiDAR and vision data in forest imaging and remote sensing. The role is part of a three-year project
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25 Sep 2025 Job Information Organisation/Company UNIVERSITY OF WESTERN AUSTRALIA Research Field Computer science Mathematics Physics Researcher Profile First Stage Researcher (R1) Country Australia
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with perovskites, CIGS, OPV and Si for large area cells or modules. Their true sustainability, cost effectiveness and how they are integrated into circularly economy are also of research interests within
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UNSW UNSW isn’t like other places you’ve worked. Yes, we’re a large organisation with a diverse and talented community; a community doing extraordinary things. But what makes us different isn’t only what
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fully resolved single-fracture simulations to large-scale discrete fracture network (DFN) upscaling. Your work will directly address high-value industry challenges in energy and resource systems. CML is