734 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" research jobs in United States
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Sciences Directorate, at Oak Ridge National Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) and machine learning/artificial
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microscopy methods (darkfield, photothermal, ultrafast, interferometric), electron microscopy, machine learning and other advanced statistical methods. Required Application Materials Cover letter, curriculum
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 5 hours ago
should have a strong background in data science, machine learning, remote sensing, wildfire science, or a related field. Experience with deep learning frameworks, satellite observations (e.g., Sentinel
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SPECIFICS Postdoctoral Scholar of Machine Learning and Statistical Genomics Description: The Department of Public Health Sciences at the Penn State College of Medicine in Hershey, Pa is seeking postdoc
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and/or cutting edges machine learning techniques to make foundational discoveries in reproductive medicine. The annual salary for this full-time position starts at $76,383, dependent upon skills and
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or interest in the use of artificial intelligence, machine learning, or computational tools in behavioral and experimental economics is appreciated. Strong emphasis will be placed on demonstrated research
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clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A
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connectivity and graph-theoretic analyses Familiarity with MR sequence programming (Siemens or GE platforms) Machine learning / AI applied to neuroimaging data EEG acquisition and analysis Use of neuroanatomical
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education. Connections working at Princeton University More Jobs from This Employer https://main.hercjobs.org/jobs/21923150/2025-postdoctoral-research-associate-ai-machine-learning-for-analytical-and-forensic
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models to characterize agricultural and ecological systems; Experience in applying advanced Artificial Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and Experience in