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for interacting with colleagues and stakeholders. Department Specifics: Develop various machine learning and data mining models including convolutional neural networks (CNNs), Transformers, large language models
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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applicants for employment without regard to race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital
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, for enhancing light trapping in nanostructured thin-film solar cells. Your role will focus on developing and applying large-scale electromagnetic simulations to identify optimal nanostructured light-trapping
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optimization, for enhancing light trapping in nanostructured thin-film solar cells. Your role will focus on developing and applying large-scale electromagnetic simulations to identify optimal nanostructured
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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post Doctoral Scholar Department: Engineering
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position in big data analysis, substance use, neurocognition, and tobacco regulatory science. The position entails research on (1) analysis of big data using advanced statistical methods, (2) assessment
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genomic analyses on large case-control cohorts to identify risk and response associations for diseases of interest. Performs integrative analyses of other molecular and omics data, such as gene expression
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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the world-class Danish registries as well as international data sources to assess pharmacological questions in large populations. The translational pharmacology group aims to understand variability in drug