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-cell transcriptomics, or spatial tissue profiling data, and are keen to develop new methods, for example using machine learning. You have a proven track record of independent research funding and high
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, methodologies, and tools in both molecular biology and computer vision. In addition, the Center—currently comprising three resident professors, one associate professor, three postdoctoral researchers, and ten PhD
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comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced statistical methods. Supported by
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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for advancing the teaching of Statistics and Data Science and for the excellence of our undergraduate program, with large numbers of majors and popular joint programs in statistics and machine learning and
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
missions (e.g., Surface Biology and Geology - SBG). This could involve advancing atmospheric correction, dimensionality reduction, or machine learning approaches for handling big data in order to improve
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/training. Preferred Qualifications: Demonstrated skills (or ability to learn quickly) in any of the following: programming (especially Python), data science, machine learning, and statistics. Previous
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cybersecurity expertise with modern AI techniques such as machine learning, deep learning, or large language models? Then we strongly encourage you to apply. You will join an established team with 25+ members
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Applicants must hold a degree corresponding to a Norwegian doctoral degree in biostatistics, statistics, machine learning, mathematics, data science, computer science or another relevant field. Doctoral
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are available at http://ist.gmu.edu/students/current-students/course-syllabi/) : Graduate Big Data Analytics Natural Language Processing Machine Learning Data Mining Cybersecurity Cyber-Human Systems Artificial