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presentation of analysis results. The ability to work with large and complex datasets. Excellent spoken and written English skills. Experience in machine learning, predictive modeling, and/or Bayesian methods
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machine learning and AI for clinical decision support. Develop, train, and validate predictive and explainable models using large-scale clinical registry data. Work closely with clinical collaborators
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positions: Qualifications 1. Computational Biology & Data Integration Using multi-omics microbiome analysis, single-cell transcriptomics, and machine learning–based biomarker prediction models, this project
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of compressible flow regimes, including supersonic and hypersonic flows, as demonstrated by application materials. Familiarity with machine learning or data-driven modeling approaches in fluid dynamics, as
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Internal Number: JR90686 Position Summary This position will focus on integrating high-resolution field monitoring, remote sensing, and statistical and numerical modeling approaches to improve predictive
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, applied mathematics, or a closely related field, awarded no more than three years prior to the application deadline*. Documented research experience in machine learning, AI, or statistical modeling. Proven
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imagery). Experience in building data models using Python or other statistical and/or mathematical programming packages. Proficiency in developing machine learning algorithms to analyze spatial-temporal
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research in causal representation learning, inference, and discovery; advance explainable models that enable discovery of image-based markers predictive of future disease evolution; and build fair, robust
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, computer science, bioengineering, data science, or a closely related discipline. • Demonstrate advanced proficiency in artificial intelligence and machine learning, particularly in applications involving
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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and