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computing, edge computing, service computing, and distributed storage systems. Design and develop novel algorithms and system frameworks for cost optimization, latency reduction, auto-tiering, caching, and
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the LLM effectiveness. Key Responsibilities: Research and develop novel ML-based methodologies and algorithms for multilingual and multimodal LLMs. Working closely with other Postdoc/RA/PhD students
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and navigation algorithms for robot in complex environments. Key Responsibilities: Responsible for development of robust and reliable sensor fusion algorithms for localization and navigation algorithms
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machine learning by designing and developing innovative models and algorithms. Key Responsibilities: Designing and conducting comprehensive research in artificial intelligence and machine learning, with a
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. Explore cutting-edge advancements in AI and relate it to the main research objective. Experimentation & Implementation Assist the team in developing and implementing related algorithms, models, and
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. The successful candidate will assist in developing novel algorithms and integrating them into robotic platforms, helping to push the boundaries of embodied intelligence in both research and practical deployment
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learning algorithms to support research in IDMxS. The Research Associate will apply/ improve/ develop machine learning algorithms to process (e.g., classify, predict) data/ images collected by IDMxS
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algorithms for UAV networking and management Implement and test the algorithms under realistic scenarios Evaluate performance of the proposed algorithms and compare the algorithms with benchmarks Publish the
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analysis tools for package and chip access, imaging and security assessment. The CA team researches the design and development of advanced algorithms and tools for automatic and efficient analysis of VLSI
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(PIM) architectures, particularly leveraging emerging memory technologies such as ReRAM Implement and optimise hardware acceleration solutions for scientific computing algorithms (e.g., iterative solvers