303 linked-data-"https:"-"https:"-"https:" positions at Monash University in Australia
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motif, hence renders the identification of the binding protein difficult. Here we propose for the first time to apply the Bayesian information-theoretic Minimum Message Length (MML) principle to optimise
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on clinical, genomics and functional dependency data (CRISPR, drug screens). Brain tumours represent the second most common cancer and the most common solid tumour in childhood in general. Paediatric brain
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with public sector decision-makers, industry partners and experts across the climate movement. Translate complex information into powerful, audience-ready insights that influence policy and spark action
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On their own, traffic accidents cause 1.3 million fatalities every year – and improper situational awareness is often a major cause. This project aims to exploit big spatio-temporal data to design
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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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an Australian citizen, an Australian Permanent Resident or a New Zealand citizen. For further information, please follow the link for each Graduate Research Degree ● 3291 - Doctor of Philosophy ● 3292 - Master of
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, for instance, utilise conversational agents, computer vision, mixed reality, wearables etc. Disability, Technology, and Society: Research with a sociological or anthropological focus on the use of bespoke and/or
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multidisciplinary cohort of clinicians and researchers based at Monash Newborn and Department of Paediatrics. The Monash Newborn research group also has a close link with the Ritchie Centre at The Hudson Institute
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and influence diverse stakeholders, build high-performing teams, and use data to inform decisions and optimise performance. Importantly, you are motivated to drive positive change. About Monash
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information about behavioural patterns, but scoring this manually is time consuming. For this reason, machine learning solutions have been developed to automate behavioural prediction [5-12]. DeepLabCut [5] is