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experiments for months before the value of output y is measured for some given input x. This creates an exciting challenge for AI researchers to develop smart algorithms that can find the optimal value of input
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techniques to design new and efficient algorithms that can provide strong protection during the entire life cycle of ML models used on the devices. Research Task I: Investigate ML algorithms and optimisations
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We are excited to offer a fully funded PhD position at the Faculty of Engineering, Monash University (Australia). This project focuses on developing new algorithms to equip social robots with
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learning, algorithms, and programming. Prior exposure to reinforcement learning or human-robot interaction is highly desirable, though motivated candidates with a strong grounding in AI/ML and willingness
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This PhD project focuses on the design and evaluation of hybrid quantum–classical algorithms for large-scale data analytics and optimisation problems. The research will investigate how quantum
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queries, and automating data transformations. By combining advancements in natural language understanding, algorithm synthesis, and debugging, the proposed framework will enable developers to efficiently
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This Masters or PhD project aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and
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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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This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
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from Analytical Spectra Hybrid Quantum–Classical Algorithms for Scalable Data Systems and Intelligent Analytics Authorised by: Marketing, Faculty of IT , Monash University . Maintained by: Marketing