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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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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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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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AI/ML for Object Tracking and Sensor Fusion, you will develop next-generation algorithms that power intelligent aerial systems—enabling real-time object tracking, multi-sensor data fusion, and
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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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, or spatial relationships of objects—and to indicate when it is unsure about its input. Key expected outcomes include the creation of monitoring algorithms that identify early signs of performance issues, and
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as required in accordance with the relevant curriculum objectives. Responsibilities include the identification of student needs and goals, and the organisation of student learning activities based
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achieve program objectives. Ability to communicate effectively, seek understanding and ask questions to clarify meaning. The path to Adelaide University We are on an exciting path to Adelaide University as
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shared objectives and align efforts toward common outcomes. Workshop organisation and facilitation: Design and lead both in-person and virtual workshops, ensuring inclusive participation and productive
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Civil Engineering team. The ideal candidate will have a strong track record of research, relative to the career opportunity in the application of advanced materials such as fibre-reinforced polymer (FRP