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research programme focused on the Impact of Human Futures on Australia’s Net Zero and Digital Transitions, funded by a Prestigious five-year Australian Research Council Laureate Fellowship awarded
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This project draws on a recent Dagstuhl Seminar (https://www.dagstuhl.de/en/program/calendar/semhp/?semnr=18322) that brought together leading experts from industry and academia, including those who
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Neuro-symbolic AI combines the strengths of neural and symbolic methods to efficiently learn and reason over models of the world. Typically, many of the assurances that can be provided by
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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Dowe, 1999a) ensures that - at least in principle, given enough search time - MML can infer any underlying computable model in a data-set. A consequence of this is that we can (e.g.) put latent factor
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systems and swarm robotics. The project builds on well established computational and mathematical modelling techniques to achieve its aims. Departure points will be agent-based simulations, optimisation
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computer skills with experience using Microsoft Word, Excel and PowerPoint; and specific experience in working with a range of data management/analytical software. Prior experience, knowledge and expertise
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DNA or RNA motif discovery is a popular biological method to identify over-represented DNA or RNA sequences in next generation sequencing experiments. These motifs represent the binding site
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Neuro-symbolic AI combines the strengths of neural and symbolic methods to efficiently learn and reason over models of the world. Typically, many of the assurances that can be provided by
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to contribute to novel encapsulation methods, optimize formulations, and characterize systems using advanced analytical techniques. You will collaborate with interdisciplinary teams to explore applications in