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Field
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to communicate with other researchers and staff in person, on the telephone and by e-mail. Vision capable of viewing gauges, computer monitors, charts, forms, text and numbers for prolonged periods. Must possess
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, Astronomy, or a closely related field is required. Experience with HPC systems, machine learning, and GRB monitor data analysis would be an advantage. Additional Information Applications must be submitted
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external) How to Submit Application Materials: To begin the application process, please send an email using the subject line “Postdoctoral Position in Machine Learning for Advancing Mental Health” to Tina
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in Biomedical Engineering, Medical Physics, Electrical, Computer Engineering or a
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rise (SLR) and flooding. Integrate field data (e.g., salinity, nutrient levels, soil and water properties) into the development of numerical models to enhance predictive accuracy. Apply machine learning
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), sexual orientation, or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas
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for healthcare. The Alsentzer Lab is an interdisciplinary research group in the Department of Biomedical Data Science at Stanford University. Our mission is to leverage machine learning (ML) and natural
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) in the department and in the Great Plains IDeA-CTR network, and growing institutional strengths in AI, machine learning and clinical informatics. This is a unique opportunity to translate and expand
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basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI