584 computer-science-quantum-"https:"-"https:"-"https:"-"https:"-"https:"-"Univ" positions at Monash University
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
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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 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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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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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.
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Stark and Geals Science Scholarship Achieving Potential Support Scholarship Allan and Pam (nee Geals) Stark graduated from Monash University during its first decade of student intakes. They believe