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, combining data from various sensors such as LiDAR, cameras, IMUs, and wheel encoders. Implement and optimize path and motion planning algorithms, including obstacle avoidance and trajectory generation. Work
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atomic force microscopy and optical spectroscopy Collaborate with theoretical researchers in the design and optimization for new fundamental excitonic effects Record, manage, and store collected data in
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Optimization models. Strong programming skills in Python. Good English writing and communication skills for research work. Independent and team player. We regret to inform that only shortlisted candidates will
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be required to lead a project under a larger research programme between Singapore and China. The candidate should fulfill the following responsibilities: Design, perform, and optimize experiments with
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Responsibilities: Conduct programming and software development for big data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations
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to optimize marketing efforts, analyse performance data, and ensure alignment with business objectives. The position is also responsible for developing, curating, and managing a diverse range of literary events
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. Develop and implement OFDMA systems with optimized bit- and power-loading for high-rate data communication. Explore spread-spectrum communication techniques with state-of-the-art codes for secure C&C
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learning-driven approaches for material design, predictive synthesis optimization, and high-throughput data analysis. Develop novel synthetic methodologies and characterization approaches for advanced
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the College’s physical space inventory, including academic offices, research laboratories, and shared facilities. Work with Schools and central units to understand space requirements and propose optimal space
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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