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; expertise in several of the following: life cycle assessment, life-cycle cost analysis, pavement simulation, machine learning, deep reinforcement learning, and/or physics-informed modeling frameworks; and
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breeding program. This requires a Ph.D. with excellent knowledge and skills in drones / UAV / UAS data collection, processing, statistical analyses, AI (machine learning, deep learning) and subsequent
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
Demonstrated research experience in machine learning, deep learning, medical image analysis, computer vision, biomedical data science, or a closely related area. Strong programming skills in Python and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 16 hours ago
Demonstrated research experience in machine learning, deep learning, medical image analysis, computer vision, biomedical data science, or a closely related area. Strong programming skills in Python and
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Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning
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, Chemistry, Physics, Applied Mathematics, Materials Science, Chemical Engineering, or a related technical field. Demonstrated research experience in machine learning or deep learning for scientific
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Job Description Here's a Glimpse of the Job The Postdoctoral Research Associate will be involved in developing deep learning architecture for multi-object data integration, federated learning approaches
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-scale human datasets. You will: - Build and apply machine learning and deep learning models to multi-scale (cells, brains, patients), multi-modal (omics, biosensor data, vision, electronic health data
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activities. This is an exciting opportunity to work within a collaborative group with deep expertise in silicon detectors, Trigger/DAQ (TDAQ) systems, software, and computing. The Argonne ATLAS group plays a
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motivated individual with experience in deep learning and a PhD in computer science, electrical engineering, biomedical engineering, biomedical informatics, biostatistics or a related discipline. Required