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Field
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and future directions within the field of human-computer interaction with a strong overview of how machine learning and/or probabilistic modelling/active inference can be integrated in it. A3 Evidenced
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We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
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algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating interpretable insights through novel analytics and
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Australian National University | Canberra, Australian Capital Territory | Australia | about 9 hours ago
: Bayesian Machine Learning – Led by Dr Thang Bui, this project focuses on sequential decision-making and bridging deep learning theory and practice. Applicants with expertise in probabilistic modelling
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key properties of quantum machine learning models—expressivity, generalization, and adversarial robustness, and the inter-play between them. These foundational insights will guide the design of novel
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leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models—expressivity
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computing, and database development and management. Background in computational modeling and machine learning. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully
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are demonstrated knowledge related to acoustic modelling, measurement and soundscape. o Essential are demonstrated data analytic skills, ideally with machine learning or statistical modelling • Other general
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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collaboration with the world-leading Briscoe lab at the Francis Crick Institute. It is using mathematical and machine-learning methods to study the early development of the neural system and developing those