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implementation of machine learning models for health analytics projects, focusing on early detection of Alzheimer’s using health and financial data, and building deep learning models to detect fake images, audio
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machine learning pipelines for protein design, including data preprocessing, model training, and validation protocols Analyze protein structure-function relationships using computational tools and databases
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-learning experiences through experiential learning. This position inspires discovery and experimentation, connecting Georgetown’s art, technology, and business communities with new models of innovation in
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new models of innovation in an environment where they can work together to solve problems and learn from each other. A critical aspect of this position involves collaboration with makers from all areas
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machine learning model development; Experience designing research projects and managing project delivery; Experience processing, documenting, and analyzing data sets; Ability to excel in a highly
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gases. This project will involve the development of sophisticated computer models of these emissions as well as on-the-ground measurements (i.e. flask sampling) around the globe. The offices of the HFC
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of sophisticated computer models of these emissions as well as on-the-ground measurements (i.e. flask sampling) around the globe. The offices of the HFC Monitoring Project will be at the newly renovated GU Capital
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improve the world's understanding of global emissions of highly potent greenhouse gases. This project will involve the development of sophisticated computer models of these emissions as
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scientists and software engineers to ingest (ETL) structured and unstructured datasets into Google Cloud Platform, apply Natural Language Processing (NLP), Machine Learning (ML), predictive modeling, and other
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Language Processing (NLP), Machine Learning (ML), predictive modeling, and other advanced techniques to evaluate hypotheses and derive data-driven insights Communicating, in written and verbal formats, CSET’s data