721 machine-learning-"https:"-"https:"-"https:" Postdoctoral positions in United States
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a team-oriented research environment. PREFERRED QUALIFICATIONS Prior experience in one or more of the following areas: longitudinal data analysis, survival analysis, spatial methods, machine learning
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languages such as R, Python, Matlab. Familiarity with software development best practices (e.g., unit testing, version control). Familiarity with inferential statistics and machine learning. Expertise in
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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research, covering research topics including, but not limited to Crop Modeling, Machine Learning, Artificial Intelligence (AI), Internet of Things, and Big Data analysis for Precision and Prescriptive
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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on developing machine-learning surrogates for electronic structure and electrostatic potential and using these models to predict structural and electronic evolution under applied bias. Methods may include density
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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, biophysics, or in a related interdisciplinary field. Experience with AI and machine learning tools is preferred. Applicant instructions: Applicants should be prepared to upload the following documents when
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, graduate students, and recent graduates to learn about policy analysis projects across various focus areas. These areas include Domestic Energy Policy, Power Sector, Critical Minerals and Materials
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to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Generally Monday – Friday, 8a-5p with some flexibility Job Summary This position is designed to have 70% clinical time, 15