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photogating effect and low-dimensional material photodetectors. 2. Theoretical Knowledge: Deep knowledge of semiconductor physics, physical optics, semiconductor device physics, optics and optoelectronics, and
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Mathematics, Algorithms and Social Media Analytics Excellent knowledge in deep learning frameworks, e.g., PyTorch, Tensorflow, Nengo Good written and verbal communication skills in English Familiarity with non
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junior researchers in the team. Qualifications A PhD degree in Computer Science or related field. Evidence of good research in computer vision and deep learning. A good publication record. Mentoring
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. Qualifications The candidate should possess a PhD degree in computer science or a related discipline, and a strong publication record in natural language processing, deep learning, or related areas. Strong
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. Qualifications The candidate should possess a PhD degree in computer science or a related discipline, and a strong publication record in natural language processing, deep learning, or related areas. Strong
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. Qualifications The candidate should possess a PhD degree in computer science or a related discipline, and a strong publication record in natural language processing, deep learning, or related areas. Strong
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forecasts of extreme rainfall, particularly related to convection, in urban environments. • Development of deep generative machine learning models to improve radar-based rainfall nowcasting in Singapore
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including OpenCV, Pointcloud library, Tracking filters, Computer vision techniques Experience with AI, deep learning and machine learning algorithms such as YOLO and Faster RCNN Experience with SLAM
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, information extraction, dialog tree generation and knowledge discovery using state-of-the-art NLP approaches. Experience with deep learning-based information retrieval, and/or deep generative natural
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). The Research Fellow will work closely with the Principal Investigator (PI) on one or more research projects. The candidate will join the research team in the areas of Deep Learning and Interpretable Graph