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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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(PIM) architectures, particularly leveraging emerging memory technologies such as ReRAM Implement and optimise hardware acceleration solutions for scientific computing algorithms (e.g., iterative solvers
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locomotion. Key Responsibilities: The successful candidate will: develop locomotion and local motion control algorithms for humanoid robots, implement learning-based and/or model-based control methods (e.g
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algorithms and system frameworks that optimize cost, performance, and scalability. The role focuses on leveraging machine learning and reinforcement learning to enhance storage and service efficiency under
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on embodied intelligence. The role will focus on developing, designing, and implementing novel algorithms and models to address emerging problems in embodied intelligence, such as Vision-Language-Action (VLA
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algorithm design. To seek and demonstrate practical utility of using AI for automating quantum algorithm design. To analyze complex wave-based physical systems and their high-dimensional parameter spaces in
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algorithms to extract biologically relevant crop traits from image and climate data, supporting mechanistic models for optimised light use and energy-efficient growth. Working closely with a modelling
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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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at NTU. Key Responsibilities: The successful applicant will be responsible for Geometric modelling for shape analysis and robotics Designing, implementing, and testing algorithms Engaging in scientific