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learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP, BLIP) or scene-graph inference is a plus. Key Competencies Strong software development and debugging skills. Able
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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at NTU are looking for a Research Fellow (RF) to carry out research in probabilistic machine learning and GenAI, by exploring cutting-edge approaches such as sequence model design, continual learning
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robots, robotic manipulators, or locomotion systems. Knowledge of machine learning, reinforcement learning, imitation learning, or computer vision techniques for robotics applications. Strong analytical
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teams. Job scope: • Research o Develop research questions, study designs, and analysis plans using SPHS data. o Conduct statistical analyses, longitudinal modelling, or machine learning approaches as
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offers a friendly and international work environment Learn more about CQT at https://www.cqt.sg/
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offers a friendly and international work environment Learn more about CQT at https://www.cqt.sg/
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offers a friendly and international work environment Learn more about CQT at https://www.cqt.sg/
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offers a friendly and international work environment Learn more about CQT at https://www.cqt.sg/
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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