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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities
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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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on projects at the intersection of computational neuroscience and machine learning. This position is part of a multi-investigator grant on the role of memory in intelligence systems. The Postdoctoral Fellow
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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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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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the use of modern machine‑learning methods within applied mathematics—particularly physics‑informed learning, anomaly detection, data‑driven modelling, and the construction of surrogate models grounded in
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of induced pluripotent stem cell-based human disease models 2) Understanding the role of immunity during tumorigenesis as well as disease relapses in order to design novel inhibitors, CAR-T cell therapy and
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experience) in applied mathematics, physics or engineering, and strong, up-to-date specialist knowledge in analytical and numerical spray modelling and machine learning. Experience with OpenFOAM or similar CFD
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of childhood allergic diseases. The candidate will develop machine learning–based biomarker prediction models to identify microbiome-derived signatures associated with allergy risk and immune tolerance outcomes
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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