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-
Machine Learning without Centralized Training Data”, https://ai.googleblog.com/2017/04/federated-learning-collaborative.html [2] “Learning with Privacy at Scale”, https://machinelearning.apple.com/research
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information on our practice-based PhD program, please see: https://sensilab.monash.edu/work-with-us/practice-based-phd/
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of everyday scientific practice [2]. We will use a combination of game theoretical models, AI and simulation techniques, as well as available data from scientific publications, citations, and science
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Dani (Senior Talent Advisor), via talentsupport@rmit.edu.au or visit our Careers page for more contact information - https://www.rmit.edu.au/careers RMIT is an equal opportunity employer committed
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Dani (Senior Talent Advisor), via talentsupport@rmit.edu.au or visit our Careers page for more contact information - https://www.rmit.edu.au/careers RMIT is an equal opportunity employer committed
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health-related field Experience with mixed methods research, systematic reviews & data analysis Strong communication and organisational skills Australian citizenship or permanent residency (If applicable
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, talentsupport@rmit.edu.au or visit our Careers page for more contact information - https://www.rmit.edu.au/careers RMIT is an equal opportunity employer committed to being a child safe organisation. We
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Status: Closed Applications open: 16/12/2024 Applications close: 23/02/2025 View printable version [.pdf] About this scholarship Description/Applicant information Disclaimer -This Scholarships is
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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(Deadline 8 March) through Melbourne Scholarships using this link: https://unimelb-scholarships.smartygrants.com.au/SFA Once you have submitted your online Financial Aid Grant application, please complete