603 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" positions at Monash University
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process natural language problem descriptions and translate them into executable code. This research seeks to streamline workflows across diverse domains, from software engineering to data engineering
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their performance evaluated in terms of classification accuracy, computational speed, and overall usability. Required knowledge Deep learning (CNNs, Transformers) and computer vision Knowledge distillation for model
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resident Australian humanitarian visa holder You must meet the following criteria: A student commencing a Mathematical Sciences Honours Program in the Faculty of Science at a Monash campus in Australia. Must
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their performance both empirically and through controlled user studies. Required knowledge Strong background in computer science in general Familiarity and understanding of basic principles underlying automated
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In collaboration with people from Monash materials engineering, neuroscience and biochemistry we are developing living AI networks where neurons in a dish are grown to form biological neural
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principles must the task choice be based for this to work? These questions are central to explaining the organisation of natural societies, from insects to humans, and to engineering self-organised systems
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-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images
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. Wallace", Computer Journal, Vol. 51, No. 5 (Sept. 2008) [Christopher Stewart WALLACE (1933-2004) memorial special issue [and front cover and back cover]], pp523-560 (and here). www.doi.org: 10.1093/comjnl
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Current reseach is in the areas of: Development of biomimetic structures as ultrasound contrast agents Deep tissue imaging using photoacoustic contrast agents All optical photoacoustic sensors for tomagraphic imaging in tissue Neural network correction of distortions in acoustic transducers web...
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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.