666 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions at Nanyang Technological University in Singapore
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or electrochemical system PhD in Chemistry/Materials Science/Physics Encourage initiating activities on MOF development, devising, and analytical process Experience in machine learning will be preferred Good oral and
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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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focusing on the integration of machine learning, wafer-scale synthesis of materials. The role will contribute to the university's research mission by conducting fundamental research, helping secure external
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Engineering, Mechatronics, Computer Science, etc. Strong background in AI, Vision Language Model, end-to-end autonomous driving, deep learning, computer vision, robotics and automation. Candidates having
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Proficiency in ionic liquid handling and techniques Excellent written and verbal communication skills Ability to work independently and as part of a team Experience with machine learning in engineering is
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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 . We are seeking a pedagogically
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, machine learning, and life cycle assessment, we aim to create sustainable wearable systems to enhance human well-being. For more details, please view https://www.ntu.edu.sg/mse/research . We are seeking a
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking to hire a research fellow (postdoc) to undertake a project to develop efficient AI and Machine
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epitaxy (MBE) Develop innovative approaches to accelerate MBE materials development using in situ characterization & machine learning Integrate epitaxial synthesis with exfoliated two-dimensional materials
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computational electromagnetics and electromagnetic simulation techniques. Experience in AI-based RF transistor modelling is highly desirable. Solid knowledge of machine learning algorithms and their application