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causal inference in heterogeneous data environments, addressing the challenge of enabling trustworthy causal analysis across distributed datasets while preserving privacy. The successful candidate will be
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, or distributed swarm algorithms would be advantageous. Experience Experience integrating sensing, localisation, navigation, communication, control, and decision-making components within a robotics or autonomous
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intellectually stimulating environment to enable high quality work in strategic directions that are of significant impact to industry, science and technology. For more details, please view https://www.ntu.edu.sg
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learning, physical AI, and spatial AI. The RA will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the Physical Vision
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Autonomous Systems and Control to develop efficient, performance-guaranteed distributed control methods leveraging cutting-edge learning algorithms and AI techniques. The Research Associate is expected