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Field
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-based or machine-learning/AI-based climate modeling (e.g. hydrometeorological and/or atmospheric processes) are particularly encouraged to apply. Position 3 Working with Dr. Kelly Baker , EEH Associate
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data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity
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, machine learning, geographical information sciences, and many other topics to help frame and solve the above problems on a national and global scale. The successful candidate will contribute to cutting-edge
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Substantial programming skills using Python or modern C/C++ Experience with machine learning and deep learning libraries Experience building AI models in platforms such as TensorFlow, Keras, or PyTorch
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decays, searches for supersymmetry and other new phenomena, and measurements of rare standard model processes. We vigorously pursue the use of machine learning techniques for data analysis. Candidates must
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, computer science, artificial intelligence, or a related quantitative field Experience with mathematical/statistical modeling and/or machine learning/Al methods Strong interest in infectious disease epidemiology
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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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when extending an offer. The ideal candidates will hold a PhD, have multiple years of prior research experience using a model organism, and a track record of peer-reviewed publications. Prior experience
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, designing natural language interfaces for more intuitive navigation of the BDC environment, creating BDC-specific foundation models, and enabling large language models (LLM) and machine learning-based
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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