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that preserves object identity or style. They should have a solid publication record in top-tier computer vision conferences such as CVPR, ICCV, or ECCV, and demonstrate proficiency in deep learning frameworks
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. The University of North Georgia is currently accepting applications for a Data Science Intern - Institutional Student Worker. This position will: Learn how to apply statistical and machine learning techniques
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programs and ability to learn new ones. Commitment to inclusive excellence. Pay Range Minimum $27.30, Midpoint $32.50, Maximum $37.70 Salary is based on related experience, expertise, and internal equity
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the research activities of Pratt Institute under one roof in the Brooklyn Navy Yard (BNY). Since our founding in 1887, Pratt has upheld the belief that education should be accessible to all who wish to learn. As
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models, artificial intelligence, Bayesian models, data visualization, dynamic causal models, dynamic systems models, item response theory, large language models, machine learning, mixture models
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, and machine learning experience; and (c) some research publication experience. Knowledge of Arabic language is preferred, but not required. Previous work on Arabic NLP is preferred but not required
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How
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Learning, or a related field. A Master’s degree is preferred. ASR/TTS Expertise Experience in training and fine-tuning Automatic Speech Recognition (ASR) or Text-to-Speech (TTS) models, preferably in
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, the USA, and internationally; providing implementation support and training for agencies using the CARE model; delivery of training and agency-specific workshops for Therapeutic Crisis Intervention agencies
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) hydrological/hydraulic modelling of urban streams and adaptation measures for current conditions and future climate scenarios. The results from the project will contribute to better estimations of how urban