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Field
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The ECE Department at NUS is seeking a Research Fellow to support applied AI research in failure analysis and fault isolation. The successful candidate will focus on developing and integrating
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initiatives, we educate and prepare future medical leaders and practitioners as part of our mission to ignite positive changes in the quality of health across the world. The CAUSALab in the Department
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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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contribute to sustainable and democratic development and be an attractive and inclusive place to study and work. ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click
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. The successful candidate will pioneer new algorithms for graph-structured data, revisit classical graph problems through the lens of modern machine learning, and help define the next generation of generative
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point cloud techniques for geometric analysis; (b) develop and implement algorithms for 3D perception; (c) design and execute experiments to evaluate validate and refine algorithms and systems; (d
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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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. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic modeling
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required to develop and demonstrate single-photon light detection and ranging (LiDAR) systems by integrating in‑house single‑photon detectors. The role will assess various LiDAR configurations, optimize
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language models, multimodal generative AI, and related areas. Develop algorithms, architectures, and training methods for world models, LLMs, and multimodal AI systems. Design methods for prediction