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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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Intelligence, or a closely related discipline. Strong research background in AI and machine learning, with a focus on efficient or accelerated models. Proven experience with model compression techniques, such as
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical
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advance research in computer vision, machine learning, and/or robotics for the digitalization, monitoring, and automation of civil infrastructure. The role will focus on developing innovative methodologies
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Engineering, or related field. Research experience with Artificial Intelligence/Machine Learning/Large Language Model. Publication track record in a series of top tier conference papers e..g, in NeuRIPS, ICLR
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/Research Fellow(SRF/RF) to carry out research in robotics and machine learning by exploring cutting-edge approaches such as learning-based robot perception, adaptive control with reinforcement learning
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scientific leaders and researchers. Job responsibilities The project aims to advance the use of machine learning techniques to model and understand plasma turbulence in magnetically confined fusion plasmas
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operations, such as data storage, budgets, expenses, assets, and ethics approvals. Key Responsibilities: Conduct independent and collaborative research applying AI and machine learning techniques
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in empirical analysis using econometric, machine-learning, and language-modeling techniques. Conducting literature reviews and synthesizing existing academic research to support ongoing projects