627 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"CUBO"-"CUBO" positions at Monash University
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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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Number offered One per year See details Zhafira Ratna Aulia MRS Resident Advisor Scholarship As an international student from Indonesia, the Monash scholarship has been a lifeline, easing my financial
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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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with living costs during study. Funded by Monash University, these scholarships support both domestic and international students undertaking Research Doctorate and Research Masters degrees at a Monash
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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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people who discover them The Opportunity The Faculty of Engineering, Department of Mechanical and Aerospace Engineering, is seeking an exceptional Research Fellow – Acoustic Sensing to join an innovative
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for up to three training scholarships in health economics within the PACE program. The successful candidates will undertake a tailored training program in theory and methods relevant to WP-1 or WP-2
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with generous top-up scholarships. We're looking for talented students with a background in mathematics, computer science, statistics, economics, engineering or other related fields. These positions
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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.