648 computer-science-intern "https:" "https:" "https:" "https:" "DESY" positions at Monash University in Australia
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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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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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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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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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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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coordination. Key responsibilities include: Providing professional administrative support across departmental operations Coordinating seminars, workshops, internal grant schemes and events Supporting committees
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100 per year See details Bachelor of Computer Science Moksh Receiving a scholarship has been my motivation to study harder. It has also given me more confidence in my studies, and pushed me to achieve
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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.