622 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" Postdoctoral positions in United States
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positions: Qualifications 1. Computational Biology & Data Integration Using multi-omics microbiome analysis, single-cell transcriptomics, and machine learning–based biomarker prediction models, this project
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&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of
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: The Postdoctoral Associate will assist the Principal Investigator, Dr. Hwan Kim , in the department of Microbiology and Immunology. Please visit the Kim Laboratory to learn more about our department/research
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and mathematical modeling, hierarchical statistical modeling, machine learning, remote sensing, geospatial statistics) • Demonstrated ability to conduct independent research and publish high-quality
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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have access to state-of-the-art technologies in multi-omics single-cell sequencing and Hi-D flow cytometry. The project focuses on the role of B cells, plasma cells, and (auto)antibody responses in
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machine learning methods. Provide theoretical predictions to guide experiments, and atomic-scale physical understanding to experimental observations. Publishing findings in peer-reviewed journals
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Candidates should have a PhD in physics or a related field, and will be evaluated on their academic credentials and their prior research record. Preferred Qualifications Experience with machine learning (ML
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Bacterial genetics for multiple species of organism Required Special Knowledge, Skills, and Abilities: Good communication and computer skills. Open approach to defining a problem and designing a strategy for
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for design consideration. Irradiated mechanical property prediction models and property correlation metamodels will be developed considering traditional and machine learning approaches. Extrapolation will be