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learning algorithms to support research in IDMxS. Key Responsibilites: Apply/ improve/ develop machine learning algorithms to process (e.g., classify, predict) data/ images collected by IDMxS. Help supervise
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on computer vision. The role involves developing and advancing novel algorithms for emerging challenges in computer vision, including continual learning and few-shot learning. The candidate is also expected
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testing data Development of machine learning models for battery health assessment and remaining useful life prediction Job Requirements: PhD degree in Electrical Engineering or related subjects. Expert
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related field At least 1 year of relevant experience in signal processing and machine learning. Good written and oral communication skills Proficiency in ANSYS, and lab test skill Ability to work
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Job Description Job Alerts Link Apply now Research Assistant in Quantum Algorithms and Machine Learning University-Level Unit: Centre for Quantum Technologies Faculty/Department-Level Unit
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advanced machine learning, with a focus on recommendation systems, graph neural networks, and multimodal AI, by designing novel models and methodologies, and leveraging large-scale structured and
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of collaborators spanning CERM, NUS, Imperial College London, Ashoka University, the Communicable Diseases Agency Singapore (CDA), the National Environment Agency Singapore (NEA), the Machine Learning & Global
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and Mathematical Sciences | NTU Singapore We are looking for a Research Fellow to study quantum materials via Machine Learning. The role will focus on develop Machine Learning technique to help DFT
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, imbalanced-data, or distribution-shift settings. Job Requirements: PhD in Computer Science, Data Science, or a closely related field. Strong research background in machine learning and artificial intelligence
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). Proficiency and independence in developing Python‑based machine learning / artificial intelligence models (e.g., LSTM or time-series models) to predict the long-term properties of bioactive materials (mandatory