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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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What makes a machine conscious? This PhD would be at the intersection of Philosophy, AI and neuroscience. You would study the latest neuroscience based theories about how consciousness emerges in
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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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PhD Studentship Description: The studentship will be based at Monash University Monash Medical AI Group led by Associate Professor Zongyuan Ge. The successful candidate will join a multi
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in analogue formats in the first place. However, the preservation of information is often a neglected aspect of community informatics projects and of information behaviour research. This PhD project
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I work on a wide range of topics with my local group and in collaboration with members of three large international collaborations. The central focus of my research is to understand how the observed pattern of fundamental particles and forces emerged, using information carried by gravitational...
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faced by real people and creating a lasting impact. Join us and help to create a world that is more inclusive and equitable. If you are interested in undertaking a PhD with MATS and you meet the criteria
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representations complicate transparency and compliance checks with data protection and privacy legislation (e.g., GDPR) whether performed by humans or computer systems. Second, both privacy-preserving distributed
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. This program of work will engage three PhD students, each from a different background (technical, psychology, design/HCI), to contribute their expertise towards enhancing the helpline service and improving
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comparing models with entirely different structures and parameter counts, whether comparing linear regression against mixture models or decision trees. MML is strictly Bayesian, requiring prior distributions