818 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"Cardiff-University" positions in Singapore
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computer science, Computer Applications, Engineering or related field At least 8 years of relevant experiences in similar role / technical hands-on experience with distributed systems, cloud platforms, and real-time
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Nanyang Technological University (NTU) has launched the “Care, Serve, Learn” (CSL) initiative as a compulsory, credit-bearing course series for all undergraduates admitted from Academic Year 2025
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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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the Office of Information, Knowledge and Library Services (OIKLS). Reporting to the University Librarian, this role is about helping shape the future of how students and faculty learn and teach at NTU
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The Institute for Pedagogical Innovation, Research and Excellence (InsPIRE) drives NTU’s commitment to excellence in teaching and learning. We champion the integration of artificial intelligence
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skills In-depth knowledge relevant to the project domain (including algorithms, systems, data structures, machine learning). Demonstrated capability to conduct innovative research. Ability to design and
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Learning (Undergraduate Programmes), this position is responsible for academic planning, curriculum coordination, and operational efficiency within NTUpreneur’s undergraduate offerings. The role ensures
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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Young and research intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU Singapore has launched the “Care, Serve, and Learn” (CSL
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical