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(e.g., finite element or wave propagation simulations) for defect detection and materials analysis Integrate AI, machine learning, and robotics into NDE and manufacturing processes for automation and
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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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expertise in climate science, hydrology, earth and planetary science, and physically-based or machine-learning/AI-based climate modeling (e.g. hydrometeorological and/or atmospheric processes
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Demonstrated ability to conduct independent research in neuroscience Strong background in in vivo mouse models, mouse surgery and behavioral procedures, mouse handling and colony management, histology
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and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep learning, and data modeling techniques. Preferred Qualifications: Prior working experience with EHR data, machine
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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Laboratory seeks a postdoctoral appointee to join a multidisciplinary team developing complex systems models, including agent-based models, and new algorithms and tools for machine learning and optimization
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conduct policies about other schools at Duke University. Compliance with all applicable University and departmental policies and procedures. The postdoc candidate is expected to: 1)Development of machine
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) and spatial Machine Learning (ML) models Salary and full employee benefits are offered in accordance with Princeton University guidelines. The Term of appointment is based on rank. Positions
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. Position Responsibilities Develop and implement machine learning and deep learning models to analyze and interpret high-throughput functional genomics data, such as ChIP-seq, RNA-seq, and ATAC-seq