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This research focuses on developing and evaluating methodologies for the optimal design of control charts within the framework of Statistical Process Control (SPC). The study aims to determine the
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the construction of PRS and enhance disease prediction. Students will gain experience in: Statistical genetics and GWAS methodology Machine learning approaches for high-dimensional data Algorithm development and
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the development of Explainable AI Systems that can provide explanations of AI agent decisions to human users. Past work on plan explanations primarily focused on explaining the correctness and validity of plans. In
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Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a
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data infrastructure necessary for collaborative research into, and development of, analytical techniques and algorithmic models. The Faculty of Information Technology has a mission to advance social good
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. This project aims to develop VR/AR applications that allow users to explore protein structures interactively and immersively, enhancing comprehension of protein function, behavior, and their roles in food
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Intelligence This project works with leading researchers in the Faculty of Pharmacy to develop new artificial intelligence technologies to aide discovery of drugs to treat pharmacoresistant epilepsy. You can
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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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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without
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algorithms for computing MML solutions beyond the one-dimensional case. Extend existing dynamic programming approaches to higher-dimensional problems or develop novel approximation methods that preserve