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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 27 days ago
machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern thinking, connecting decades of computer science methodologies with modern data and
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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for spatiotemporal data (e.g., CNNs, LSTMs, Transformers, or Graph Neural Networks). Hybrid modeling: Experience with physics-informed machine learning or the integration of ML with data assimilation/multivariate
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application development. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data
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managing large multimodal datasets, as well as contributing to analytical studies related to machine learning, clinical decision rules, and time-to-intervention evaluations. Responsibilities include curating
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collaborators. Mentor junior colleagues and students. Write, present, and publish research findings in peer-reviewed journals. Knowledge and Experience Requirements: PhD degree in statistics, computer sciences
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support of Division scientific goals · Collaborate with staff implementing advanced data pipelines, including applications of machine learning and AI for clinical prediction and identification of novel
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sheet evolution, methane hydrate fluxes, or applying machine learning to geosciences to reconstruct glacial histories and project future ice sheet behavior. Please read this interview for more details
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The postdoctoral fellow will lead and co-lead projects that combine computational modeling, machine learning, and EEG to answer questions about scene understanding and neural representation. The fellow will work
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publication record. Outstanding data analytics, mathematical, and computer modelling skills. Excellent interpersonal communication and oral presentation skills in English Self-driven and strong team spirit Open