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of mobile ringtones. Traditional machine learning methods and transformer models will be used to learn patterns from audio signals and classify ringtones into predefined categories (e.g., default ringtones
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Monash University-Vietnam Government PhD Scholarship (Project 89) This joint scholarship program supports high-achieving Vietnamese candidates to undertake a PhD at Monash University. Applicants can
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Monash University - Museums Victoria PhD Research Scholarship The Robert Blackwood partnership is a collaboration between Monash University and Museums Victoria to encourage and facilitate new
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MD-PhD Industry Leaders Scholarship (for returning MD-PhD students) Industry Leaders Scholarship This scholarship is awarded to Monash University medical students who have demonstrated a commitment
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or nats, balances model complexity against goodness-of-fit. It is essentially a formal implementation of Occam's razor. A key advantage of MML is that the message length provides a universal gauge for
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The primary objective of this project is to enhance Large Language Models (LLMs) by incorporating software knowledge documentation. Our approach involves utilizing existing LLMs and refining them
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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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, mainly in the area of search-based software testing to verify that the AI components of self-driving cars work as they should. This project is in collaboration with Professor Hai Vu and the Monash
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This project is technical in nature and would suit a candidate with a background and interest in #Java programming, health informatics or health data (or a combination thereof). The primary aim of this work is the extend and localise (to the Australian context) the open source Synthea stack....
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the shortcomings of these techniques, deep learning is more and more involved in static vulnerability localization and improving fuzzing efficiency. This project aims to deliver a smart software vulnerability