422 machine-learning-"https:"-"https:"-"https:"-"https:"-"Iscte-IUL" 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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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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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
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This research project aims to address the critical need for privacy-enhancing techniques in machine learning (ML) applications, particularly in scenarios involving sensitive or confidential data
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significant step forward in machine translation capabilities. However, "NMT systems have a steeper learning curve with respect to the amount of training data, resulting in worse quality in low-resource settings