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data (PET, CT, Magnetic Resonance Imaging with Late Gadolinium Enhancement – MRI-LGE) and clinical variables. The approach encompasses unsupervised multimodal registration, three-dimensional deep
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? No Offer Description Segmentation of scenes and shots for multimedia content monitoring and analysis using artificial intelligence and deep learning techniques, including transition detection, key
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at the forefront of medical science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding
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. ●Deep knowledge of political science, public policy, and/or Arizona history. ●Knowledge of preservation and conservation standards for archival materials. ●Demonstrated effective interpersonal and
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(pore sizes below 100 nm) structures. Excellent scintillation properties, particularly a high radioluminescence light yield. Maximal transparency to ensure that luminescence flashes can be detected deep
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to diverse academic and industrial audiences. Proficiency in Python and deep learning frameworks such as PyTorch. Experience with Linux environments and GPU cluster management is essential. Competent in
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and dental care programs, generous retirement benefits, and a wide array of family‑friendly and cultural programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/ Choose Duke. Join
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explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The successful candidate will need to be eligible for UK security clearance in principle
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or equivalent Skills/Qualifications Technical Skills: MATLAB programming. PCB design. Specific Requirements Knowledge: Neural networks / Deep learning. Acoustics. Vibrations. AI: Artificial Intelligence
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of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fueled by curiosity and a deep sense