1,148 network-coding-"Chung-Ang-University"-"Chung-Ang-University" positions in Australia
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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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and Community Trust for a Just and Effective Net Zero Transition , a two-year, multi-region, mixed-method study focused on the role of trust in Australia's decarbonisation efforts. The project
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This project is similar in flavour to the Conscious AI project but rather than come from a Philosophical/Neuroscience/Math/Theory angle, this project aims to build self-aware neural networks
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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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plants they visit and pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing
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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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Australian National University | Canberra, Australian Capital Territory | Australia | about 13 hours ago
at the John Curtin School of Medical Research (JCSMR), within the ANU College of Science and Medicine. This role will lead the development of advanced deep learning frameworks—including graph neural networks
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This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in three unique
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This project focuses on brain network mechanisms underlying anaesthetic-induced loss of consciousness through the application of simultaneous EEG/MEG and neural inference and network analysis