367 computer-security "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "Dr" "Dr" uni jobs at Monash University
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), human movement/performance and aquatic culture (including diving) is desirable. This work is in collaboration with Dr. Sarah Jane Pell (sarahjanepell.com). The candidate will engage with water and motion
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This project draws on a recent Dagstuhl Seminar (https://www.dagstuhl.de/en/program/calendar/semhp/?semnr=18322) that brought together leading experts from industry and academia, including those who
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employment is contingent upon the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University. Enquiries: Dr Louisa Picco, Research Fellow, +61
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various skin condition/s. Relevant resources: DOI: https://doi.org/10.1007/978-3-031-43987-2_20 DOI: https://doi.org/10.1007/978-3-031-43907-0_54
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analysis. Additionally, experience in healthcare informatics, user experience research, and a commitment to improving mental health services are highly desirable. Project funding Project based scholarship
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people who discover them The Opportunity Lead a dynamic program of veterinary care, research animal skills training and scientific services at the Monash Animal Research Platform (MARP). At the centre of a
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interested in, please apply via our website and complete the online expression of interest form https://www.monash.edu/ research-ethics-and-integrity/ animal-ethics/accordion- content/accordion_1 For further
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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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wastage. These improvements should provide significant benefits, such as reducing severe losses due to cybercrimes and enhancing national security for Australians. [1] Darban, Z. Z., Webb, G. I., Pan, S
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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