665 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" 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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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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journals and conferences Good research experience in AI and machine learning as well as wireless networking Independent, highly analytical, proactive and a team player Excellent teamwork and verbal, written
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an emphasis on technology, data science and the humanities. We are seeking a highly motivated Learning Technologist to join our Digital Learning team, with a strong focus on curriculum content development and
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As part of NTU’s Learning & Talent Management team, you will play a pivotal role in shaping NTU’s enterprise‑level people development narrative in support of the NTU2030 vision. This role is about
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/Research Fellow(SRF/RF) to carry out research in robotics and machine learning by exploring cutting-edge approaches such as learning-based robot perception, adaptive control with reinforcement learning
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for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations of the designed algorithms and systems. Help with research
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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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, and system integration Providing general support for the lab Job Requirements: Master’s degree in Electrical Engineering, Computer Science, or related field Knowledge and experience in machine learning
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scheduling and resource allocation problems for machine learning pipelines deployed in safety-critical cyber-physical systems. Close collaboration with PhD students involved in the project. Participate in