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of artificial intelligence, machine learning, human language technology, human computer interaction, data mining, database, privacy, and high-end computing. Responsible for program design and implementation
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Department of Biomedical Informatics is a highly dynamic and multidisciplinary environment that has strengths in bioinformatics, global health informatics, imaging informatics, machine learning, mHealth
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bioinformatics, modeling, and machine learning to join our lab. Our research uses a multiscale approach to study the immune response to emerging/re-emerging viral infections. We study the dynamics of virus-host
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for biochemical assays to understand the functional consequences of these variants. The successful candidate will also have the opportunity to learn advanced biochemistry and structural biology methods. KEY
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research approaches. Working closely with nursing partners and clinical collaborators, our exciting work combines non-invasive imaging technologies, deep learning, computer vision, and clinical workflow
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precision medicine algorithms for critically ill patients using EHR data. We are looking for a full-time data analyst with proficiency in R and python, and the ability to take machine learning projects from
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simultaneously and meet multiple deadlines with flexibility to accommodate changing needs and priorities. Computer skills using Microsoft Office applications required as well as ability to learn and use program
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datasets. Advanced skills in machine Learning, data analysis, and model implementation using R and/or Python. PhD in a health-related discipline required. Candidates with backgrounds in pharmacy
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bioinformatics, modeling, and machine learning to join our lab. Our research uses a multiscale approach to study the immune response to emerging/re-emerging viral infections. We study the dynamics of virus-host
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data cleaning, preprocessing, and quality control for large-scale imaging and proteomic datasets; developing and implementing statistical and machine learning models; and preparing summary figures