454 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" positions at Monash University
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Current federated learning architectures in mobile healthcare are limited to a centralised model without considering the full continuum of mobile-edge-cloud. Additionally, to support different data
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mechanical loading of such samples. The focus of the PhD project will be to use machine learning techniques to better understand the interplay between the crystal orientations and deformation patterns in a
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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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testing code, and learning from feedback. 🔍 Research Objectives Design an Agentic SWE Framework Model an AI system that combines reasoning, planning, and self-correction for software engineering tasks
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financial, personal, and confidential information. This project seeks to introduce machine learning and artificial intelligence techniques to effectively detect phishing websites. By leveraging these advanced
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Learning Support Officer Job No.: 684376 Location: Clayton campus Employment Type: Part-time, fraction (0.8) Duration: Continuing appointment Remuneration: $96.768 - $104,450 pa HEW 6 plus 17% super
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
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Professor and Senior Academic Director, Learning and Teaching Job No.: 680070 Location: Clayton campus Employment Type: Full-time Duration: Continuing appointment Remuneration: A competitive
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Candidates should hold a previous degree (Bachelor’s and/or Master’s) in Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering, with demonstrated knowledge in machine
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The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes