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focused on using advanced numerical methods to explore low energy dynamics in strongly interacting quantum spin systems. The candidate will develop and implement advanced algorithms to investigate
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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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The Centre for Urban Solutions is to provide leadership in developing innovative solutions and sustainable technologies for space creation and urban infrastructure development. The School of Civil
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peer-reviewed journals and/or top-tier conferences. Knowledge & Skills: Strong foundation in machine learning, deep learning, and algorithm development. Proficiency in scientific programming (e.g
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Responsibilities: The candidate will study theoretically forward and inverse uncertainty quantification problems for partial differential equations, and multiscale partial differential equations. He/she will develop
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international collaborators across clinical, academic, and industry settings to develop privacy-preserving machine learning approaches, federated learning frameworks, and interpretable algorithms for multimodal
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edge-assisted offloading strategies for IoT networks. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is
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for three highly motivated Research Fellow to join Associate Professor Xia Kelin's team at the School of Physical and Mathematical Sciences. The project focuses on developing Mathematical AI techniques
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of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep
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characterization of integrated memristor devices and systems. • Develop algorithms and system-level integration strategies to harness the capabilities of AI accelerator for machine learning and deep learning