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. This study aims to construct a transparent, non-invasive predictive framework combining machine learning and explainable AI (XAI) to differentiate malignant from benign pelvic masses, stratify patient risk
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data provides opportunities for advanced Machine Learning (ML) approaches. Research Aim This PhD research aims to develop advanced Machine Learning methods for prediction, risk stratification, clinical
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the high latitude ocean. A tool for both understanding and prediction of these processes is the next generation of the NASA Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS
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is intended not merely to apply existing AI models, but to advance research that integrates AI prediction models, generative models, data assimilation, and ensemble forecasting while accounting
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unsupervised learning (e.g., regression, classification, clustering), natural language processing (NLP), and ensemble methods (e.g., Random Forest). Demonstrated expertise in business and strategic analytics
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. Demonstrated knowledge of Machine Learning & AI, including supervised and unsupervised learning (e.g., regression, classification, clustering), natural language processing (NLP), and ensemble methods (e.g
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on lncRNA structure. These experimental constraints will then be used to guide deep learning-assisted RNA 3D structure prediction tools, in order to generate ensembles of structural models. Clustering and
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that integrate structural predictions and neutron scattering data using ensembles instead of current single structure implementations. The integration of simulation and experiment will yield methods that can be
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promising results in building prediction models, they are typically data-centric, lack context, and work best for specific feature types. Interpretability is the ability of an ML model to identify the causal
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for regional numerical weather prediction (NWP) system. The role will focus on exploring and adding new space-based observations in the next-generation NWP system jointly developed by the Climate and Weather