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, physical AI, and spatial AI. The RF will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the Physical Vision Group’s long
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Fellow to work
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, developing, and controlling an avian-inspired robot capable of precise and agile flight in urban environments. The role will focus on merging advanced computational modeling, AI-driven control algorithms, and
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on Embodied AI Safety. The role will focus on designing, developing, and implementing novel algorithms and models to address emerging challenges in Embodied AI Safety, including attack and defense mechanisms
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on world model. The role will focus on developing, designing, and implementing novel algorithms and models to address emerging problems in world model, Multimodal Large Language Models and Video Diffusion
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synthesis Earth system model new module integration, scenario simulations, and prognostics analyses Physics-informed deep learning/hybrid modeling/reasoning AI algorithm development and optimization Job
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system model new module integration, scenario simulations, and prognostics analyses Physics-informed deep learning/hybrid modeling/reasoning AI algorithm development and optimization Job Requirements: A
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research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in
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on integrating an agentic platform for electrocatalyst discovery and developing novel machine-learning algorithms (e.g., reinforcement learning) for materials discovery and process optimization. The candidate will
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, converter control, and energy systems. Design, model, simulate, and develop advanced power electronic converter topologies and associated control algorithms. Investigate high-efficiency and high-power-density