674 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions at Nanyang Technological University
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, Chemical Engineering or related disciplines. Careful and systematic in laboratory work. Reliable and able to follow experimental protocols. Willing to learn and work independently after training. Preferred
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of “Research Assistant” for a research project related to statistical learning of time-series models. The successful candidate will work with Hemant Tyagi (NTU Singapore) and Chew Lock Yue (NTU Singapore) in
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, Tan Tock Seng Hospital and the National Centre for Infectious Diseases. This position will offer a multidisciplinary and unique collaborative environment with diverse learning opportunities
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or more of these areas (e.g. mice/rodent handling, optogenetics and behaviours, animal surgery and dissection, calcium imaging, gnotobiotic studies and microbiome analysis, etc). Lead, assist or learn in a
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of being An Institute of Distinction: Leading the Future of Education and our mission to Inspire Learning, Transform Teaching and Advance Research. Read more about NIE here . NIE invites suitable candidates
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learning opportunities, which includes student-led activities, leadership development initiatives, residential hall programmes, integration efforts, community engagement initiatives, as well as arts 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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stakeholders both externally and internally to positively impact on the programmes and their expected outcome. Explore and leverage on the use of innovation to optimize student’s learning and employability
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the learning, teaching and research needs. The successful applicant will support the Service Innovation and Excellence unit within the Library in driving service quality initiatives. Responsibilities
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. The long-term aim of this work is to develop a framework focusing on mediational factors and learning outcomes in makerspace. This evidence-based framework may then be used by makerspace owners and staff