457 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" research jobs in Singapore
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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
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/ machine learning / statistics on spatial and single-cell omics (transcriptomics, proteomics, epigenomics, metabolomics, meta-transcriptomics, etc.) data. Independently carry out computational and
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international law. More on CIL can be found here: https://cil.nus.edu.sg/ About the Oceans Law and Policy Team: Ocean Law & Policy is one of CIL’s core programme areas and was established over 10 years ago. It
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in empirical analysis using econometric, machine-learning, and language-modeling techniques. Conducting literature reviews and synthesizing existing academic research to support ongoing projects
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and interpretable machine learning systems. The successful candidate will work on projects involving ensemble learning, large-scale data analytics, and high-performance model design, aimed at developing
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scientific leaders and researchers. Job responsibilities The project aims to advance the use of machine learning techniques to model and understand plasma turbulence in magnetically confined fusion plasmas
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Computer Engineering, Computer Science, or a related field from a prestigious institution. Extensive experience in deep learning, AI, computer vision, 3D reconstruction algorithms, and large-scale Pre
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aims to improve electrodialysis (ED) for REE separation by developing advanced membranes and integrating AI-driven optimization techniques. By combining materials innovation with machine learning
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that delivers real-time, hyperlocal information on urban heat risks in tropical cities. Leveraging Doppler lidar–based microclimate studies and machine learning, the research emphasizes vulnerable groups
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enrichment (GO, KEGG), network analysis, genome assembly and binning, systems biology, and multi-omics integration. Apply statistical modelling, machine learning, and deep learning approaches for biomarker