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Australian National University | Canberra, Australian Capital Territory | Australia | about 3 hours ago
University. Located within the School of Art and Design, the Design program combines contemporary design methods and digital technologies with hands-on making. It prepares graduates who are skilled, inventive
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/ machine learning algorithms to support research in the IDMxS Analytics Cluster. The RF will apply/ improve machine learning algorithms to process (e.g., classify, predict) data collected by IDMxS. Help
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. We have an exciting opportunity for an enthusiastic and motivated postdoctoral Computational Biologist to contribute to multimodal data integration as part of a translational genomics programme within
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School of Mathematics and Physics Full-time, fixed-term position for up to 2 years Base salary will be in the range of $114,824.05 - $136,048.72 + 17% Superannuation (Academic Level B) Based at our
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, nearly 12,000 faculty and staff and 350,000+ living alumni, UC combines a Top 35 public research university with a physical setting The New York Times has called “the most ambitious campus design program
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physics, and computer science. We seek candidates who possess excellent professionalism and enthusiasm in their work, good communication skills which promote positive interactions in the lab, strong ability
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 4 hours ago
-centered ML, or NLP. Supported by an ARC Future Fellowship and CSIRO-NSF project. Computational Analysis of Online Economies – Led by Prof Lexing Xie and Dr Yun Kuen Cheung, this research explores digital
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-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements. § Implementing algorithms
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access to state-of-the-art analytics and a robust cross-functional scientific community. The Opportunity: You will be part of the Genentech post-doctoral training program that provides an outstanding
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It