510 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at National University of Singapore
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and course materials. Evaluate module assessment components. Teach up to 240 contact hours per academic year. Qualifications A Bachelor’s or Masters’ degree in a relevant discipline. Candidates must
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and course materials. Evaluate module assessment components. Teach up to 240 contact hours per academic year Qualifications A Bachelor’s or Masters’ degree in a relevant discipline. Candidates must have
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research program to develop next-generation sensor devices and systems for human-machine interactions. Qualifications PhD in Materials Sciences, Robotics, Mechanical Engineering, or related disciplines. More
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and positive learning experience for our Graduate Programme students by: Handling full spectrum of programme applications, from submission through assessment (including interviews & tests), offer
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and course materials. Evaluate module assessment components. Teach up to 240 contact hours per academic year. Qualifications A Bachelor’s or Masters’ degree in a relevant discipline. Candidates must
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on new initiative and emerging technologies. • Conduct or facilitate knowledge sharing. Qualifications • A degree in Computer Science, Computer Engineering, Information Technology or equivalent. • Relevant
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Teaching): Deliver day-to-day technology and audio-visual support for a high-quality teaching and learning experience. Deploy and support hybrid teaching technology (eg. Zoom) supporting either fully virtual
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units across the University. This position offers excellent learning and development opportunities and on-the-job application of data analytics and leveraging on emerging technology, analytical and AI
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invites you to join our team At NUS-ISS, we don’t just teach AI, we help organizations adopt it responsibly and effectively. You will be part of a vibrant community of educators, innovators, and industry
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of Lecturer / Senior Lecturer and teach inter-disciplinary courses in the College, in the areas of innovation & entreprenurship, digital literacy / AI, and / or systems thinking. Each inter-disciplinary course