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validate wearable data algorithms, software tools and pipelines supporting large-scale, multi-cohort research. It will contribute to the ProPASS federated data analysis platform, including testing
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into an accessible and practical digital resource. Applications are encouraged from candidates with the technical expertise and research focus to make a valuable contribution to this project. Monash University seeks
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to the design and empirical evaluation of a large-scale field experiment, including household, market and value-chain surveys, quantitative analysis, and the development, testing and implementation of a digital e
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professionals providing excellent frontline support to Monash University students, eExam Supervisors, and the broader eAssessment Operations Team during the delivery of end-of-semester exams. The primary focus is
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practices, including cloud-native architecture, CI/CD, AI-enabled development, automated testing and secure-by-design principles. Proven experience leading multidisciplinary software engineering or digital
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coordination and communication skills A PhD or equivalent research experience (preferred) Experience with clinical or physiological data (desirable) About Monash University At Monash , work feels different
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problem-solving, project coordination and communication skills A PhD or equivalent research experience (preferred) Experience with clinical or physiological data (desirable) About Monash University
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PatchSentinel-X: Transformer-Based Security Patch Intelligence for Vulnerability Lifecycle Assurance
analysis into a much deeper AI reasoning problem. The final goal is to build an intelligent assistant for secure software maintenance that can say: “This patch looks incomplete.” “This fix addresses input
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, Alice has no choice but to give away her highly sensitive information. A more ideal solution is to use a PET tool to provide Alice a way to (cryptographically) prove to SerPro that she is eligible
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-route tasks to maintain uninterrupted service. This research area involves developing fault-tolerant systems that adapt to hardware and software failures. Students will work on predictive maintenance and