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Field
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: Develop novel machine learning theories and techniques for analyzing noisy time-series data, with a particular focus on seismic signals Perform uncertainty quantification in time-series analysis to assess
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are robust and not subject to significant changes due to irrelevant alterations in input data. A vital part in ascertaining this robustness is to have good methods for quantifying the uncertainty associated
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
. Position Overview The Robotics group at the ANU School of Computing is opening a 2-years Research Fellow (Level B) position to work on an exciting project in sequential decision-making under uncertainty
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
a 2-years Research Fellow (Level B) position to work on an exciting project in sequential decision-making under uncertainty for robotics. This project is a collaboration with the Australian Defence
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with machine learning techniques for robotic decision-making and intelligent control for tasks with high uncertainties. Experience with research on multi-agent collaboration and decentralized control
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for plausible metal bioleaching, biorecovery, bioprocessing, biosensing and bioremediation and compare them against conventional systems and conduct their uncertainty analysis. You will create AI models
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approaches to model uncertainty for learned computer vision systems, including dense prediction. The position will develop novel methods for deep learning in computer vision that accurately quantify their own
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to assess the performance of PIML models. § Assessing uncertainty in the predictions of PIML models. § Developing systems for multiscale modeling of atomic layer deposition processes. § Developing
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Professor Yew Soon Ong (CCDS) as a Research Fellow to contribute to a project focused on modelling and quantifying uncertainty for foundation models. You will be part of a larger project focused on developing
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servicing missions. Experience with machine learning techniques for robotic decision-making and intelligent control for tasks with high uncertainties. Experience with research on multi-agent collaboration and