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for architecting Northeastern University's transition from legacy data structures to a modern, scalable, AI-ready data architecture. This role conducts deep assessments of existing systems-including Banner, Workday
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and inference of unmeasured observables. 2. Improve computational methods to extract the CKM matrix element Vub from inclusive decays using deep learning approaches. Environment: ICCUB is a María de
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the Job which include, but are not limited to, Computer Vision, Deep Learning, Federated Learning, and Cloud Computing. Desirable: B1 A comprehensive and up-to-date knowledge of current issues and future
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to support the growth and competitiveness of our automotive designs in the global landscape. For more details, please view https://www.ntu.edu.sg/ancl Key job purpose Conduct investigations on the bonding and
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, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities
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systems, advanced sensing technologies, application of deep learning and AI for wireless systems, etc. For more details, please view: https://www.ntu.edu.sg/eee We invite applications for the position
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Electronique, Energie, Automatique (EEA) ou équivalent. Le candidat doit posséder un bon niveau en mathématique et des connaissances en traitement du signal. Des connaissances en machine learning/deep learning
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communication skills. Proficiency in developing deep learning models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in
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engineering or similar. Knowledge and experience with deep learning models applied in computer vision. Remarkable academic trajectory, validated by a strong record of publications in relevant international
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations