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and the role of key architecture components can lead to the development of more efficient and robust training algorithms. This can ultimately result in AI systems that are both more powerful and
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will focus on developing and applying Bayesian statistical models to investigate and predict biofouling patterns to enhance our understanding of how environmental factors and antifouling technologies
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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
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science conference [1]; one of our papers is recognised as Clarivate Web of Science HighCite (top 1% of papers for the field of research) [2]; three of our algorithms (TS-Chief, InceptionTime and Rocket
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group of experts to predict (probabilistically) whether these occupations will be automated, augmented or unaffected by emerging technologies. Using this data, a classification algorithm is then trained
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as generous parental leave, the option to purchase additional leave, and flexible working arrangements to support your work-life balance. We offer ongoing learning and development to grow your career
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Apply now Job no:534009 Work type:Full Time Location:Sydney, NSW Categories:Business Development / Industry Engagement Employment Type: Full-time, continuing Remuneration: Competitive total package
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, Step 6 ($113,911 + 17% Superannuation). Location: Kensington, NSW Why The Role Matters: The Post-Doctoral Fellow is expected to contribute towards the research effort of UNSW and to develop
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This PhD scholarship is funded by an Australian Research Council Industry Fellowship grant. It is a 3.5-year research training program. The ARC Industry Fellowship program aims to develop a strong