187 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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accepted until the positions are filled. All applications must be submitted electronically via the "Apply Now" button below. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/405439
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position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity
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of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Job Purpose As a University of Applied Learning
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our
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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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foundational knowledge in signal processing and machine learning. Working knowledge of computer vision and deep learning concepts, including object detection and image-based classification, with hands
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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities
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: Architect and deploy machine learning and computer vision models directly onto onboard edge devices (e.g., NVIDIA Jetson) for real-time object detection, tracking, and autonomous decision-making. Proof
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Engineering, Computer Science, Data Science, Statistics, or equivalent. Strong theoretical background in statistics and machine learning. Knowledge of the basics of federated learning and causal inference is