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Field
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, the appointed candidate will work closely with the line manager to develop novel control algorithms in EAP soft robotics combining Gaussian Predictors, hands-on laboratory experiments and JULIA computing
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Processing and Machine Learning to develop signal processing and machine learning algorithms and methods for communication networks. Key Responsibilities: Develop signal processing and machine learning
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/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming
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Rasch tables using time calibrations, and documenting and manualizing the algorithms and related products. The post-doctoral associate will be part time, 12-month employee of the University of Minnesota
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of the designed algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably Bachelor’s degree in Computer Engineering, Computer
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methods for eliciting and aggregating safety specifications and risk thresh-olds for AI systems, with a particular focus on mechanisms that provide axiomatic guarantees, are algorithmically tractable, and
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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; proficiency in graph data structures and algorithms for geometric analysis; advanced knowledge of surface representation math; experience in writing geometry translators for complex surface features; excellent
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 12 minutes ago
Data Exchange Standard (ADES); (2) modernizing short-term impact monitoring through adaptive search algorithms for systematic ranging (Scout); and (3) refining long-term impact prediction via improved
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information of the data to make a prediction using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms