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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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University Tandon School of Engineering The Dynamical Systems Laboratory at NYU Tandon School of Engineering is seeking to hire a Post Doctoral Associate to work on the mechanics of deep-sea sponges. We seek
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transportation systems and autonomous driving. • Strong understanding of generative AI, deep learning, and multimodal machine learning, with hands-on experience. • Excellent programming skills and proficiency with
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environment to study these topics given its expertise in Machine and Deep Learning, Computer Vision, Signal Processing, and Multimedia. Also, its declared vision to work especially in presence of imperfect data
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 26 days ago
Deep Learning), successful experimental collaboration experiences and excellent communication skills are preferred. Create a Job Match for Similar Jobs About The University of North Carolina at Chapel
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the measurement instrument in close collaboration with our industrial partner, Veridis Technologies. An ideal candidate has experience in vibrational spectroscopy and spectral processing. Expertise in deep learning
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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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(particularly Deep Learning), will also make it possible to leverage the collected data to enrich knowledge of ovine behavior. The candidate will join a dynamic research group within the Image/Vision team
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. Demonstrated experience in either of the following areas (a) data science, (b) theoretical nuclear reaction models and/or (c) deep learning-based machine learning and applications of artificial intelligence
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in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in