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Field
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substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding
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, STATA, SAS, or other statistical software; Exposure to pre and postprocessing of magnetic resonance imaging and/or magnetic resonance spectroscopy data or willingness to learn neuroimaging techniques
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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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learning Opportunity to support diverse and engaged student populations Innovative academic environment Comprehensive employee benefits and wellness resources Inclusive community that values diverse
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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies
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to excellence in research, education, and patient care. Learn more about Duke University's competitive benefits package. Research Areas Include Immune mechanisms of response and resistance to glioblastoma
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generating fusion energy. This research will focus on the chemical speciation and transport of tritium in the molten salt blankets using ab initio quantum simulations, machine learning potentials, and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 19 hours ago
. Examples include: determination of high-resolution shape models using shape-from-shading or novel machine-learning methods; studies of high-resolution shape models for geophysical and geological studies
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and machine-learning potentials for planetary materials. Curating and generating large-scale ab initio datasets across wide pressureâ“temperature regimes. Designing and training advanced machine