293 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" Fellowship positions in Singapore
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frameworks for advanced property prediction and analysis of inorganic disordered materials. Carry out machine-learning based first-principle calculations aimed at advancing the understanding defect-based
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multimodal data, enabling early detection and personalised interventions in clinical neuroscience. The candidate will take the lead on machine learning and computational analyses, primarily supporting our
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian You will be part of a dynamic research team working on topics relevant
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and data pipelines to enable real-time data acquisition and closed-loop control. Collaborate with AI researchers to implement machine learning models for adaptive experimental design and autonomous
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Engineering in the 2025 QS World University Rankings by Subjects. The EEE Rapid-Rich Object SEarch (ROSE) Lab focuses on research in: (i) visual search & retrieval, (ii) video analytics & deep learning, and
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Location_ONB: Kent Ridge Campus Posting Start Date: 31/10/2025 Job Description The successful candidate will work with Associate Professor Duane Loh on conducting research at the interface of Machine Learning
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digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different conditions. To propose a methodology/framework in a
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, Singapore, and the broader public. For more details, please view https://www.ntu.edu.sg/medicine/CMM . The role will involve investigating the influence of modifiable environmental risk factors, dietary and
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: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation
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insights from cutting-edge clinical and translational research. More information on the Department’s research portfolio may be obtained from https://medicine.nus.edu.sg/obgyn/. The Core Support Faculty will