339 data-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Monash University
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We have a range of potential research projects on offer in partnership with VIFM - https://www.vifm.org/ - looking at ML techniques in predicting forensic diagnoses / image analysis, across
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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
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Machine Learning without Centralized Training Data”, https://ai.googleblog.com/2017/04/federated-learning-collaborative.html [2] “Learning with Privacy at Scale”, https://machinelearning.apple.com/research
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information on our practice-based PhD program, please see: https://sensilab.monash.edu/work-with-us/practice-based-phd/
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system to unlock important information from unstructured data sources including X-ray images, surgical and radiology text reports. We will compare prediction models based on existing, routinely collected
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"A picture is worth a thousands words"... or so the saying goes. How much information can we extract from an image of an insect on a flower? What species is the insect? What species is the flower
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trends that started earlier in other time series. Part of what will be done will be to identify sufficiently similar time series - and to pool (or combine) relevant data. One of the approaches that will be
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the endless possibilities of digital sound, allowing the plucking of sounds out of thin air. URLs and Further Reading https://airsticks.xyz/ Ilsar, A.A., 2018. The AirSticks: a new instrument for live