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in Free Space-Time Job Description Demonstrate and measure the breakthrough concepts in nanophotonics using optical sources such as transmission electron microscope Develop high-impact theory
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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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Engineering Experience conducting empirical studies within the field of systems and software engineering Strong knowledge of qualitative research method (interviews, focus groups, case studies, grounded theory
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equations – strong foundations in quantum electrodynamics (QED) are a significant bonus. The role of RF will focus on developing ab initio theory and developing software to describe and study groundbreaking
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robotics systems. • Strong mathematical background with solid knowledge in numerical optimization theory. Familiarity with semidefinite programming and its convex relaxation techniques is highly preferred
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leadership role in advancing the research agenda within the group, developing new directions in cryptographic theory and practice, and mentoring junior researchers. Responsibilities include leading
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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
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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