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This project aims to identify novel methods for inferring actors, activities, and other elements from short message communications. Covert communications are a specialist domain for analysis in
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and Monash University support units. To be successful in this role you will have exceptional project management expertise and a strong track record of delivering large-scale programs within complex
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theoretical physics, particularly quantum physics, a strong publication track record, and a drive to contribute to cutting-edge research, we encourage you to apply. About Monash University At Monash , work
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to cloud-based machine learning services, on-device ML is privacy-friendly, of low latency, and can work offline. User data will remain at the mobile device for ML inference. Problems: In order to enable
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doctoral qualification (or equivalent experience) in a relevant discipline Strong quantitative analysis skills (R, Stata, or SPSS), with a track record of research outputs Experience in health services
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bring demonstrated analytical skills, a track record of peer-reviewed publications and experience in data extraction for systematic reviews or meta-analyses. Strong proficiency with software tools such as
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guarantee that what one believes to be one’s secrets will remain secret. Namely, a DP algorithm cannot ensure that private attributes cannot be inferred from publicly observable attributes if they have strong
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stakeholders. They will possess strong organisational, planning, and communication skills, with the ability to clearly convey technical concepts and policy advice. The role requires a proven track record of
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ICU care globally. About You You have a background in clinical or health research and a proven track record in project delivery. You thrive in complex, fast-paced environments and love working with
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of a GIS-Based Model for Active Citizenry Street-Level Environment Recognition On Moving Resource-Constrained Devices Bayesian Generative AI (PhD Project) Explainability and Compact representation of K