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developing innovative solutions for integrating geophysical data and machine learning approaches for geological modelling and site characterization. The position is expected to perform independent and
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, assess the health state of systems, and predict their future evolution and remaining useful life. The proposed approach integrates physics-based and data-driven modeling techniques, including machine
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About Us Georgia Southwestern State University – a four-year institution – cultivates excellence in learning and teaching that encourages intellectual, personal, and social growth for students
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Modeling and Analysis, Investment Banking, Mergers and Acquisitions, Financial Technology (FinTech), Cryptocurrency and Blockchain, Artificial Intelligence and Machine Learning in Finance, Programming
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for an Assistant Teaching Professor position in the School of Electrical and Computer Engineering. The successful candidate will be expected to teach courses primarily in computer engineering subjects with
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learning how to access campus or digital University resources, offers general directions of campus/class schedules. Occasionally, setting up meetings or booking rooms. Escalates specific questions
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of Molecular Biology (LMB), within a programme aimed at studying the neural circuit basis of behaviour. Specifically, to map the synaptic wiring diagram, or connectome, of whole brains, using machine learning
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range will be guided by the rules in the collective bargaining agreement. The salary range for this position is $43.00 - $53.94 (Hourly Rate). To learn more about the benefits of working at UCSF
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 1 month ago
modules leveraging deep learning for classical problems such as segmentation and 3D object tracking interfacing machine learning code and the robot using ROS2 contributing to the creation of datasets
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 25 days ago
) the exploration of mixed-precision arithmetic in the context of high-order discontinuous discretization methods, and (2) the integration of machine learning techniques to complement and enhance traditional