29 data-analytics-phd Fellowship positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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Schemes of Service: Research Division: Infocomm Technology Employment Type: Fixed Term Project Overview We are seeking an outstanding and highly motivated Research Fellow (PhD) or Research Engineer
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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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predict storm surges in Singapore coastlines based on different weather conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing
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should possess: PhD/Ms/BSc in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep
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, reporting, and communications with industry and research partners. Job Requirements Bachelor/Master/PhD degree in Computer Engineering, Computer Science, Artificial Intelligence, Data Science, Electrical
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Essential PhD in Bioengineering, Chemical Engineering, Materials Science, Nanotechnology, Analytical Chemistry, or related fields. Strong publication record in biosensors, nanomaterials, Raman spectroscopy
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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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operation and maintenance of equipment Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer
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robots, robotic manipulators, or locomotion systems. Knowledge of machine learning, reinforcement learning, imitation learning, or computer vision techniques for robotics applications. Strong analytical
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element analysis software (e.g., Abaqus, ANSYS). Experience with stability and mooring system design. Strong analytical skills and familiarity with data collection instruments and techniques. Excellent