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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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research fellow to support ongoing research projects in diffusion generative models and Monte Carlo stochastic simulation methods. This position holder will apply these techniques and other advanced AI
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following projects: Project #1 Title: Enhance Students' Interdisciplinary Learning through Large Language Model-Empowered Learning Analytics (MOE TRF 2/25 ZG) Project #2 Title: Building an Eco-system
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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interactions in the extreme ultraviolet (EUV) regime Develop new, efficient software for modeling unprecedented electromagnetic phenomena, using languages such as C++ and Python Formulate new theories pertaining
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foundation models for general manipulation based on vision-language-action models Develop learning from human demonstration (LfD) framework for vision-language-action models Develop multi-embodiment
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data and build a 3D geological model. The position involves conducting research, supervising undergraduate students, and writing project reports and scientific articles. Job Requirements: PhD
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of efficient AI-for-Science systems, leveraging foundation models (including small language models) and parameter-efficient adaptation techniques such as LoRA, grounded in a strong understanding of optimization
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Reinforced Concrete (RC) substructures. Key Responsibilities: Simulate RC substructures under different boundary conditions. Design and fabricate test models. Develop algorithms for anomaly detections. Publish
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computing and AI models is a plus. Good written and oral communication skills, with papers published in leading conferences or journals Entry level candidates are welcome to apply We regret to inform you that