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Field
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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internationally known, unique facilities. This team has developed state-of-the-art experimental and computational models for solving water resource problems worldwide. CHL research and development addresses water
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 15 days ago
: PD&PEWER Level A&B Postdoctoral - Research Fellow _ CSS.pdf This position will provide opportunities to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited
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. There are opportunities to broaden out into other areas such as new algorithm development, and advanced computational methodologies for integrated analyses. You will have a key role in planning, designing and executing a
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on heterogeneous integration and security of chiplet-based IC systems. This role involves research and development in chiplet-based architectures, aiming to demonstrate secure intelligent computing platforms
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on heterogeneous integration and security of chiplet-based IC systems. This role involves research and development in chiplet-based architectures, aiming to demonstrate secure intelligent computing platforms
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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noise, allowing only specific algorithms with relatively shallow quantum circuits to be executed. In the NISQ era, hybrid algorithms run partially on quantum computers and partially on classical computers
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. The roles of this position include: Development of algorithms to improve memory/sample/time efficiency of LLM training. Development of a workable prototype system with capabilities such as conversational