28 machine-learning-"https:" "https:" "https:" positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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imaging, biomedical instrumentation, image processing, or machine learning is desirable. Ability to follow technical protocols accurately and to maintain clear documentation of work performed. Ability
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Engineering, Computer Science, Robotics, or a closely related discipline, with foundational knowledge in signal processing and machine learning. Working knowledge of computer vision and deep learning concepts
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degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of image
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problems or enhance industry operations Computer Vision and Image Processing Machine Learning, Deep Learning, and Reinforcement Learning Large Language Models (LLMs) and Multimodal Models Generative AI
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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 development and debugging skills. Able
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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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intelligence (AI), and high-performance computing (HPC), as well as quantum-inspired algorithms and quantum machine learning (QML). Responsibilities: Lead and contribute to applied quantum computing research
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Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skills that are relevant to industry demands
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Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry-collaborative research Where to apply Website https://www.timeshighereducation.com/unijobs/listing/413018/research-fellow
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, thermal, and vibration signatures for early detection of bearing faults, winding faults, imbalance, and other equipment anomalies. Develop data analytics pipelines, machine learning models, and