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or later, but no later than December 1, 2027. This is purely a research position and will have no teaching duties. However, if desired, successful candidates may have the opportunity to teach at KAIST. A
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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, data processing pipelines, machine learning and generative AI applied to physical activity and sleep research. The position will contribute to the development of an AI-based behaviour change tool and
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Computer Science, Artificial Intelligence, Mathematics, Engineering, or a related field. Entry level candidates with demonstrated expertise in artificial intelligence (AI), machine learning, deep learning
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Architecture: Architect, build, and evaluate multi-agent systems powered by LLMs and machine learning, incorporating Orchestrator and Memory agents, vector databases, and knowledge graphs to enable complex goal
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scientific leaders and researchers. The group of Wang Zhongjian is looking for postdocs working on scientific computing and machine learning related topics. The funding is currently under a MOE grant entitled
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, Artificial Intelligence (AI) & Machine-Learning (ML) applications. Good written and oral communication skills Proficiency in power system modelling, advanced control theory (e.g., model-predictive control, etc
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science, artificial intelligence, machine learning, computational social science, data science, or a related computational discipline. Applicants must have experience with digital trace/multimedia datasets and in
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collaborative and interdisciplinary activities. Job Requirements: Preferably PhD degree in Computer Engineering, Computer Science, Applied Mathematics or equivalent. Strong academic background in machine learning
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sustainable manner. Key Responsibilities: Responsible for developing explainable machine learning algorithms for Tunnel Boring Machine (TBM) tunnelling and excavation Developing large language model enhanced