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University of Singapore is dedicated to the interdisciplinary study of humans and algorithms on the Internet, and its implications on the society of the future. This is an exciting opportunity to join us as a
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leverage their expertise to develop innovative algorithms for data analysis. Additionally, they will be responsible for communicating their findings to the scientific community through academic meetings and
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, SuperGLUE, LiveBench). Familiarity with distributed training frameworks and high-performance computing environments. We regret that only shortlisted candidates will be notified. Hiring Institution: NTU
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https://dr.ntu.edu.sg/entities/person/easonchen . We are looking for a highly motivated Research Fellow to facilitate research in using atom probe tomography (APT) to study the distribution of hydrogen in
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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
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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
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on rapid and accurate quantification of disasters using remote sensing and space geodesy. They will also advance InSAR processing algorithms to optimise change detection capability in Southeast Asia, where
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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optimization problems Develop mathematical modeling framework to find the optimal operation strategy Conduct computer programming to verify the efficiency of the designed solution algorithms Analyze data
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(OpelRT or Typhoon), electrical system design for better efficiency and system resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge