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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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framework on how to build up a generic framework to use learning-assisted approach to solve various optimization problems Develop mathematical modeling framework to find the optimal operation strategy Conduct
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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to develop and optimize scalable experimental protocols across diverse material families. This role is part of a multidisciplinary team integrating materials chemistry, machine learning, and autonomous
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of Physical and Mathematical Sciences. We are seeking a Research Fellow to contribute to the research agenda of the project ‘Geometric Optimization and Design in Learning and Robotics'. Key Responsibilities
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multidisciplinary team driving transformative sensing technologies. Key Responsibilities: Develop and optimize fabrication processes for sensor arrays based on 2D materials (e.g., graphene, MoS₂), including flexible
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: Investigating novel optical materials and technologies Developing and optimizing optical system designs using simulation tools Characterizing and testing optical system performance Collaborate with cross
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uses. To investigate feature-level just-noticeable difference modelling for machines to facilitate assessment and optimization. To formulate a comprehensive visual feature codec for machine uses
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application like drug delivery. Key Responsibilities: The Research Fellow will work on a cross-disciplinary project at the intersection of mechanics, acoustics, design optimization, and advanced manufacturing
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Responsibilities: Conduct programming and software development for data management. Design and implement machine learning models for optimizing data management. Conduct experiments and evaluations of the designed