395 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" positions at Monash University
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, intelligent components learn their decision logic from data corpus in an end-to-end manner and act as a black box. Without rigorous validation and verification, intelligent solutions are error-prone especially
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Statistical Methods, Automated Planning and/or Reinforcement Learning.
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awardee. The Opportunity Generative artificial intelligence is a significant and highly visible use of machine learning which has become commonplace in a matter of a few short years. Without common
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in diverse, real-world environments. Both classical machine learning methods and deep learning techniques can be employed to tackle this task. This project aims to achieve several objectives: 1
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to detail, accuracy, and understanding of confidentiality principles Well-developed communication skills, with experience drafting documentation and reports High level of computer literacy, including
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learning to guide the self-aware learning and network formation. As such this expected to be a purely mathematical and computational project. To do this project you would need to apply for a Monash
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science, AI, software and cybersecurity, human-computer interactions, and nature-positive innovation Enjoy a supportive academic environment that values creativity, rigor, and societal relevance About
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is one of the most powerful drivers of learning success. Despite decades of research affirming the value of feedback, it remains underutilised and inconsistently effective. A key reason for this gap is
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include supporting students throughout their rural medical training through the delivery of tutorials, practical classes and small group learning, while fostering personal, professional and academic
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tutorials practical classes and small group learning while ensuring curriculum and assessments align with contemporary clinical practice and rural healthcare contexts. This is a fixed-term position for three