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understanding of non-stationary complex systems through theoretical analysis and numerical simulation develop efficient statistical algorithms for analyzing and inferring dynamical models from multivariate time
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research group. The successful candidate will be expected to make a vigorous contribution in one or more of the following research areas and contribute to the supervision of PhD and MRes research students
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dataset analysis to develop novel approaches to understanding impacts on fish life history of urbanised seascapes and consider impact and restoration trajectories. The project will involve significant
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the following key capabilities: A PhD in a relevant field Demonstrated experience working with ecological datasets Demonstrated experience in statistical inference and reporting Knowledge of models and theory in
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to the Research Stream 3 Lead and has no direct reports. Responsibilities: Responsibilities in this role include but are not limited to - Develop models for mortality, morbidity, and aged care risks