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Position Capabilities of the position description . For more information regarding this position, please contact Yee Lian Chew Please see here for our Reconciliation Action Plan Please see here for our
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design, molecular biology, and data-driven discovery to advance understanding of human retinal disease mechanisms and support the development of new treatments. The role includes undertaking both
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on clinical trials, as well as contributing to the development of data-driven interventions and stewardship models to enhance patient outcomes after surgery. This position is an opportunity to work with a
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) environments for large-scale data analysis, including workload managers such as SLURM. For full details about this role, and other criteria, please review the Position Description . Not sure if you meet all
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to the present and modelling towards the future. Research within BEES is clustered within four general thematic areas: Ecology and Evolutionary Biology; Climate Science; Environmental Change, Sustainability and
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, artificial intelligence, or statistical modelling techniques to digital forensics, online surveillance, or large-scale data analysis, particularly in the context of wildlife crime detection and prevention
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Minimum qualification of a Master’s degree, with a PhD preferred, and demonstrated expertise in coral reef data analysis, field studies, and coral reef simulation modelling. Coding experience in Matlab or R
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of the University may be required. For further information, please refer to the Position Description linked here: Postdoctoral Research Fellow in Microbial Ecology and Crop Disease Management . Who We’re Looking
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evaluate methods via experiments, benchmarking, simulation and/or real‑world data. The successful candidate will have: A PhD in Statistics, Data Science, Computer Science, Mathematics, or a related field
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will need: A PhD or equivalent in stochastic modelling, data science, network analysis, statistics, or related discipline Is eligible to apply for an Australian Government security clearance. Research