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We are excited to offer a fully funded PhD position at the Faculty of Engineering, Monash University (Australia). This project focuses on developing new algorithms to equip social robots with
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without
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processing algorithms (desirable). Electronics design skills using Altium (desirable). About the College of Science and Engineering At the College of Science and Engineering we believe in the power of science
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Mobile and continuous health monitoring has seen major advancements in recent years. The capabilities of current mobile phones and their built-in sensors have inspired many mobile sensing
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This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
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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
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monthly stipends. This research direction will involve close collaborations with Prof Lin Chen of China. The supervisor is currently engaged in a joint research project with Prof Lin Chen that will fund
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prototype sensor. About the role Level 8 – ($127k – $143k) - plus 17% Superannuation and annual leave loading Fixed Term – 15 months Full-time (35 hours per week) The role reports to Professor Dane McCamey
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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