90 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) in United Kingdom
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Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP, BLIP) or scene-graph inference is a plus. Key Competencies Strong software
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of subjects such as computer vision, Machine Learning, Artificial Intelligence and Kinematics and dynamics. Autonomous systems, Robotics and Automation. Industry 4.0 and Internet-of-Things. Advantageous to have
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As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry in its research pursuits. This position is situated within the Centre for Immersification
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault diagnosis, and early fault prediction in electric vessels