167 postdoc-parallel-computing Fellowship positions at Nanyang Technological University
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) who is highly skilled in and deeply passionate about computational electromagnetism and mathematical physics/engineering. The SRF should have strong background in computational methods for solving
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Engineering, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, AI, etc. Strong background in autonomous driving, deep learning, interaction modelling, prediction, robotics
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Research Analyst/Senior Analyst/Associate Research Fellow (China Programme) The S. Rajaratnam School of International Studies (RSIS), a Graduate School of Nanyang Technological University, Singapore
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College of Computing & Data Science International Postdoctoral Fellow Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top
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, postdocs, and students to integrate structural biology data with biochemical and functional assays. Prepare manuscripts, conference presentations, and contribute to grant reporting and project milestones
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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supervise graduate students. Job Requirements: Ph.D. in Electrical Engineering, Computer Science, Statistics, or other related fields. Familiarity with machine learning and computer vision frameworks. Good
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. Assist PI in proposal writing and help supervise graduate students. Job Requirements: Ph.D. in Electrical Engineering, Computer Science, Statistics, or other related fields. Familiarity with machine
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necessary lead relevant meetings. To undertake any other duties relevant to the programme of research. Job Requirements: PhD degree in Computer Engineering, Computer Science, Electronics Engineering or
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems