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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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-technical audiences and engage in stakeholder or end-user consultation. DESIRED CHARACTERISTICS: Demonstrated experience in models of opinion dynamics, Bayesian reasoning models, natural language processing
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successful you will need: A PhD in geology, geochemistry or a related field. An established track record of publication in isotope geochemistry and/or critical mineral ore systems. Demonstrated expertise in
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mission is to accelerate the commercialisation of research for the Australian Defence Force (ADF), develop education training pathways, fast-track entrepreneurs' ideas to commercialisation, and enhance
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of Robotics, automation or relevant Ag-Tech solutions. A track record, relative to opportunity, of publishing in international peer-reviewed journals. Strong collaboration and negotiation skills. Demonstrated
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opportunity Experience in machine learning and deep learning Proficiency in one or more high-level programming languages such as Python, Java, or R. Strong commitment to interdisciplinary research and a track
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projects, preferably in primary care or related fields Demonstrated experience leading quantitative data analyses and the reporting of health research findings Track record of health-related publications
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to be tracked over time. This allows the location and intensity of lung disease, and its resolution with treatment, to be measured. XV produces a very rich 4D dataset (3 spatial dimensions + time
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to field test emerging AI agent-based technology and push forward projects of national significance. You will learn first-hand about the current state of drone-based surveillance, tracking and distributed
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need: A PhD in Molecular Biology, Cell Biology, Genetics, Biotechnology, or a related area. Expertise and interest in cancer and/or stem cell biology and associated techniques. Outstanding academic track