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focused on developing and applying methods for estimating the causal treatment effects on health outcomes using large health data. The Mission of the P-HOPER Center is to conduct innovative population
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. Analyzes large data sets. Analyzes next generation sequencing data (e.g., RNS-seq, whole genome/exome sequencing). Uses state-of-the-art bioinformatical and statistical tools. Develops new statistical
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Description Job Responsibilities -Analyze and interpret metagenomic data to investigate and identify often divergent viral genome sequences. -Collect, reconstruct and analyze large datasets obtain by cryo
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undergraduate or graduate students, if appropriate. Additional Information The ideal candidate should be an independent, solution-oriented thinker with a strong background in processing very large data sets
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Job Description Job Responsibilities: -Design and implement AI/ML models to analyze large-scale agricultural datasets (e.g., field trials, satellite imagery, IoT sensor data). -Develop pipelines
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collaborative research on immune development and responses to respiratory viruses. Analyze clinical and large-scale datasets (e.g., genomic, transcriptomic, proteomic data). Design and execute experiments using
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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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focus on the comparative effectiveness of drug therapies on dementia-related outcomes using large-scale observational electronic health record data and local electronic health record data. The fellow’s
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research, analyze data, and contribute to scholarly publications. You'll also prepare and present research findings, develop grant proposals, and mentor student researchers. Additionally, you'll have the
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highly interdisciplinary, integrating big data analysis, state-of-the-art machine learning models, mathematical modeling, and systems biology to elucidate the mechanisms of drug interactions in complex