422 machine-learning-"https:"-"https:"-"https:" positions at Nanyang Technological University
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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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: PhD degree in Computer Science, Computer & Electronics Engineering or other related fields Strong background and knowledge in at least one or preferably more of the following fields: Cybersecurity, Deep
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research in formal verification, machine learning and artificial intelligence system assurance. The successful candidate will develop new techniques and tools for analysing, verifying and improving
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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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, 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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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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coding skills including Pandas package, statistical or machine learning packages, access to cloud AI services Experience with cloud services and environments Experience with developing Web or mobile
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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
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computing environments and GPU computing. Proven experience in weather and climate models development and applications. Experience in machine learning, deep learning, or AI applications for atmospheric
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road safety analytics framework. The role involves integrating multi-source transport datasets, developing advanced analytical and machine learning models for risk identification, and supporting