72 structures "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" positions at Monash University in Australia
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discovery. While deep generative models have shown promise in proposing novel molecular structures, they typically require massive, cleanly labelled datasets to train effectively. In practice, acquiring high
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extract events and mine knowledge from existing unstructured/structured data, and exploit the knowledge via neuro-symbolic reasoning for crime prevention (eg -sexual assaults), especially when there is no
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This project draws on a recent Dagstuhl Seminar (https://www.dagstuhl.de/en/program/calendar/semhp/?semnr=18322) that brought together leading experts from industry and academia, including those who
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with
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maintain the transformation roadmap across initiatives; establish robust governance structures that enable speed, transparency and accountability; and lead structured program delivery through milestone
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For over a century, X-rays have been used to visualise the internal structure of opaque objects, driving major breakthroughs in healthcare, industry, and scientific research. Conventional X-ray
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networks so that they can accurately identify anomalies in the presence of concept drift. We would like to consider different types of changes in graph structures, such as emergence/deletion of new nodes
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design, contributing to our understanding of experiencing the human body as play. More information at http://exertiongameslab.org
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sensing equipment and theoretical work around play. For more information see http://exertiongameslab.org
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information see http://exertiongameslab.org