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Martin Australia invite applications for a project under this program, exploring the development of Physics Informed Neural Networks (PINNs) for efficient signal modelling in areas such as weather
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PhD Scholarship for The Impact of Future Human Values and Practices on Australia’s Net Zero and Digital Transitions Job No.: 679372 Location: Caulfield campus Employment Type: Full-time Duration
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PhD Scholarship – Modelling the social and political drivers of net zero transitions Job No.: 670767 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment
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, the internal workings of deep neural networks remain largely mysterious, posing a significant challenge to the interpretability, reliability, and further advancement of these models. This project seeks deep
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for tomagraphic imaging in tissue Neural network correction of distortions in acoustic transducers web page For further details or alternative project arrangements, please contact: alexis.bishop@monash.edu.
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numbers of minimally-interpretable models being used, as opposed to traditional models like decision trees, or even Bayesian and statistical machine learning models. Explanations of models are also needed
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networks, and a collaborative, interdisciplinary research environment.Submit your Expression of Interest (EOI) via email to Dr Madeline Sprajcer at m.sprajcer@cqu.edu.au as soon as possible. Please feel free
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the demographic profiles and contact networks of the individual simulation model will be drawn from Virtual WA: a geospatial analysis platform built in-house by A/Prof Cameron and Camilo Vargas at The Kids. Student
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to simulate sewer networks as dynamic systems, targeting ≥90% modelling accuracy. Train an explainable decision-making agent to optimize interventions (e.g., pipe upgrades), balancing cost, equity, and
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success for reactions that involve a net gain or loss of electrons: electrochemical reactions. These are an important class of reactions as they can be driven directly by renewable electricity, contributing