16 computer-science-image-processing Fellowship positions at Nanyang Technological University
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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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learning algorithms to support research in IDMxS. Key Responsibilites: Apply/ improve/ develop machine learning algorithms to process (e.g., classify, predict) data/ images collected by IDMxS. Help supervise
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machine learning, computer vision, and medical image analysis, with publications in top-tier AI and medical image analysis conferences and journals, including CVPR, ICCV, ECCV, NeurIPS, MICCAI, TPAMI, TIP
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research grants in the above areas Job Requirements: A PhD degree in Computer Science, Data Science, Engineering, or a related field. Research experience in Computer Vision, Image Processing, Multimedia
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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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Characterisation Materials Science, Computational Materials Science, Composite Materials, Functional Composite Materials, Energy, Nanomaterials, Low Dimensional Materials, Biomaterials Materials, Bioinspired
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We invite applications for a Research Fellow to join an interdisciplinary research team led by Dr. Sing Yian Chew (NTU). The successful candidate will contribute to an ongoing research program
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: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation
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on the developed models for agencies/commercial partners Supervise junior researchers and master students Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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of PhD/Masters/FYP students. Job Requirements: Preferably PhD in Computer Science, Electrical & Electronic Engineering, or equivalent. Background knowledge in signal representation/processing, esp