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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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applied physics other related disciplines. Demonstrated knowledge in at least one of the following areas: porous media flow computational fluid dynamics (CFD) pore-network modelling lattice Boltzmann method
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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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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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on Wajarri Yamaji Country in remote Western Australia, using cutting-edge technology to process vast volumes of scientific data and deliver transformational insights into the Universe. The Computing and
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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 Opportunity Join the School of Computer Science and Engineering in the Faculty of Engineering at UNSW as a Lecturer / Senior Lecturer in a Teaching and Research role. In this role, you will contribute
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Convertible Tenure Track or continuing appointment Location: Kensington – Sydney, Australia The Opportunity Join the School of Computer Science and Engineering in the Faculty of Engineering at UNSW as an
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The relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and
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. Wallace (1996). MML estimation of the parameters of the spherical Fisher Distribution. In S. Arikawa and A. K. Sharma (eds.), Proc. 7th International Workshop on Algorithmic Learning Theory (ALT'96