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to behavioural and population health data relevant to Singapore’s diverse communities. Develop predictive and explainable machine learning/deep learning/genAI models using multimodal cross-section and longitudinal
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to cell and gene therapy. Will learn to use advanced manufacturing tools and strategies to gain a deeper understanding of challenges associated with T cell-based immunotherapies (such as CAR-T cells). Will
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with
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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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). The ideal candidate brings a strong machine learning foundation, curiosity about sound and music computing, and enthusiasm for collaborating with PhD students and postdocs. You will help combine individual
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related
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, organised researcher who can evidence: A PhD, or equivalent in statistics, machine learning or a closely related discipline, OR near to completion of a PhD. Expert knowledge of statistical inference methods
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computational pipelines for multiplex imaging, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune
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experience in at least three of the following: developing watershed model input datasets, geospatial analysis, applying large-scale hydrologic models, artificial intelligence and machine learning, computer
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). The candidate will be working on developing state-of-the-art methodology in clinical prediction modeling, including novel uncertainty assessment method (Value of Information analysis), as well as Machine Learning