440 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" research jobs in Singapore
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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
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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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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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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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and acquire spectral data Perform Raman spectral data analysis using machine learning algorithms Work with DiSTAP plant biology collaborators, training researchers in spectrosocpy Work with local
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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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possess strong interpersonal communications skills with excellent written, oral communication and computer skills. Perform experiments with live laboratory mice, including administering treatments
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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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: 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