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Field
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-site datasets collected across international collaborators. The role will involve working closely with MRI physicists, clinicians, computer scientists, engineers and mathematicians to ensure high-quality
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, BioPermit. Training as a member of the CDC IPP, you will collaborate with computer and health scientists to develop enhancements for BioPermit and improvements to the electronic database. Additionally, you
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projects spanning data visualization, human-computer interaction, and human-centered AI. Coordinate scientific project activities, including planning, reporting, and coordination across collaborating
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for: Conducting research and development on AI-based solutions for automated defect inspection and condition assessment of train components by designing and developing deep learning, computer vision, and machine
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or individuals, Professional demeanor, high energy, dynamic personality and excellent communication and interpersonal skills, Proficiency with Microsoft Office and other computer applications, Proven verbal and
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, Educational Technology, Learning Sciences, Human-Computer Interaction, or a related discipline. Strong interest in research relating to Generative AI, AI literacy, digital learning, workplace learning, or human
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We are looking for a Research Fellow for the (SHINE) Centre 2.0 co-led by Professor Massimo Alioto, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS
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with direct industrial impact. Responsibilities The successful candidate will: Conduct cutting-edge research in Computer Vision, Video Understanding, and Multimodal AI. Design AI models for concept
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/PhD degree in Computer Engineering, Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, or related disciplines. Experience in project management, research administration
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, relevant experience in computer-based statistical analysis and presentation of results, demonstrated proficiency in a coding language used for data analysis, such as Python or R, proof of previous data