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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
interface to humans with varying expertise in real-world responsible AI scenarios. The successful candidate will design and develop new AI algorithms and systems, engage with a dynamic research group within
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of masculinity, especially in relation to younger male audiences. The successful applicant may explore such questions as: What drives engagement with manosphere communities? How do algorithmic systems and platform
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Research Associate in Logical Foundations of Planning. In this role you will work closely with Dr Rubin on research projects, and contribute to the collegial culture of the Sydney Algorithms and Computing
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formative assessment and personalised feedback while ensuring fairness, accountability, and transparency. The research will explore a combination of algorithmic design, human–AI interaction, and empirical
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algorithm that allows accurate simulation of fluid transport processes in porous media coupled with chemical reactions (e.g. dissolution and precipitation). The algorithm will be validated firstly against
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estimation methods for deep neural networks. A principled Bayesian framework for multimodal uncertainty modeling. Robust learning algorithms under missing modalities and distribution shifts. New uncertainty
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algorithms for resource-efficient hydroponics and evidence-based frameworks for integrating green space exposure for improved student wellbeing. This project will potentially enhance urban food resilience
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that operate at scale and complexity. You will apply strong software engineering practices to solve complex technical challenges, helping to bring advanced algorithms into real-world operational environments
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algorithms for computing MML solutions beyond the one-dimensional case. Extend existing dynamic programming approaches to higher-dimensional problems or develop novel approximation methods that preserve
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the given non-classical logic. The proof of the claim contains an algorithm for deciding whether an arbitrary formula is true or else false! This proof can then be exported automatically to produce a formally