112 machine-learning-"https:"-"https:"-"https:"-"https:"-"NOVA.id" Fellowship positions in Singapore
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advance research in computer vision, machine learning, and/or robotics for the digitalization, monitoring, and automation of civil infrastructure. The role will focus on developing innovative methodologies
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year of relevant research experiences in similar research role / technical hands-on experience in AI and machine learning Familiarity with large-language models Good written and oral communication skills
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international collaborators across clinical, academic, and industry settings to develop privacy-preserving machine learning approaches, federated learning frameworks, and interpretable algorithms for multimodal
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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: PhD degree in learning sciences, educational technology, human-computer interaction (HCI), information technology, AI or relevant fields. Prior experience and proficiency in educational data mining and
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical
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of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop software prototypes for AI-for-Science systems tailored to scientific discovery and data
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science development Design, develop, and validate machine learning models for skill inference, mastery estimation, and personalized feedback, including Bayesian approaches, sequence models (for example LSTM