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-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning approaches for resistome prediction or biomarker discovery is a plus. Why Join Us? Access to cutting-edge
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works to interpret genomes and distill the immensely complex networks that form the foundation of human biology and disease, through accurate machine learning models. Current areas of interest include
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projects involving multi-electrode array recordings in behaving animals, using techniques including electrophysiology, psychophysics, computational modelling and advanced quantitative analysis. This position
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) strong background in quantitative methods, statistics, computer science, geospatial data analysis and modeling; (b) experience in AI and geospatial computer version; (c) advanced skills in scientific
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transportation operations and network modelling, accessibility analysis, data analysis (statistics and/or machine learning methods), and spatial mapping. Because the work will involve multiple years of daily
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engineering. About the opportunity Play a key role in advancing the AuScope Geochemistry platform ‘EarthBank’ at UWA. Contributing to new and existing analytical datasets and data models, improving
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for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in
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to rigorously evaluate new and uncertain community-level interventions in infectious disease control. A key component relates to harnessing advanced mechanistic disease transmission models to improve prediction
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CRISPR tools to correct or model the defective genomic DNA, and further deliver these newly-engineered editors into targeted organs to correct the corresponding phenotypes. The current disease models
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. The research program embraces team science drawing from i.e., implementation science, data science, geospatial, epidemiological, and machine learning approaches to better understand broad contexts including