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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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cutting edge research work, develop novel computational tools and integrate new strategies for the safe and sustainable use of chemicals and materials. Your tasks Large-scale data analysis, programming and
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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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informatics and signal processing. Experience with large volumes of physiological and temporal medical data and time series analytics are essential. Strong programming skills in Python and modern machine
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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
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will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive
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research environment, comprising two full professors, one associate professor, one assistant professor, one postdoc, and a large number of PhD students. The project includes strong partnerships with