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on theory and benchmark development Disseminate results through scientific publications and presentations Support mentoring of junior researchers and engage in group-level collaboration Job Requirements: Ph.D
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with NTU Singapore and ETH Zurich researchers across theory and applications Job Requirements: Ph.D. in Computational Science, Geophysics, Engineering, or a related field Strong experience in numerical
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, ECCV, NeurIPS, ICML, AAAI, TPAMI, IJCV, TIP, TMM. Deep understanding of the theory of Machine Learning, Deep Learning, Computer Vision and Causal Inference. Experience in at least one Deep Learning
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quantification, explainability, and decision-making under uncertainty. We aim to push the boundaries of theory and practice in these areas, developing principled methods that address fundamental and applied
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Maxwell’s equations – strong foundations in quantum electrodynamics (QED) are a significant bonus. The role of SRF will focus on developing ab initio theory and developing software to describe and study
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Responsibilities: Explore the frontiers of intelligent sensing by advancing cutting-edge theories and pioneering transformative technologies. Integrate wireless sensing with Large Language Models (LLMs) to pioneer
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Responsibilities: To conduct independent research in deep learning theory. To produce publications in top conferences and journals. To offer guidance and assistance to any students involved in the project