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throughout the process of FL collaborative training; 2) Investigate and design security measures (e.g., robust aggregation rules) to defeat model poisioning attacks against FL; 3) Design and optimise
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specialised as-needed via fine-tuning or prompt engineering. In this project we will explore all aspects of this process with a focus on increasing trust in the model outputs by reducing or eliminating
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specialised as-needed via fine-tuning or prompt engineering. In this project we will explore all aspects of this process with a focus on increasing trust in the model outputs by reducing or eliminating
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computational project. To do this project you would need to apply for a Monash Scholarship. Required knowledge A decent theoretical background in physics, computer science, mathematics, engineering
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computational project. To do this project you would need to apply for a Monash Scholarship. Required knowledge A decent theoretical background in physics, computer science, mathematics, engineering
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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
ensure local relevance. Required knowledge Artificial Intelligence; Machine Learning; Computer Vision; Bioinformatics; Biomedical Engineering; Neuroscience; Genomics; Medical Physics; Data Science
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knowledge A decent theoretical background in philosophy, physics, computer science, mathematics, engineering, neuroscience or psychology. Project funding Other Funding reference https
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knowledge A decent theoretical background in philosophy, physics, computer science, mathematics, engineering, neuroscience or psychology. Project funding Other Funding reference https
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. This project, from the engineering perspective, aims to explore a better development process for DL, covering requirement analysis, data collection and labeling, data cleaning, network design, training
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. This project, from the engineering perspective, aims to explore a better development process for DL, covering requirement analysis, data collection and labeling, data cleaning, network design, training