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for storytelling; working with large datasets, APIs and public records; AI tools in news production and distribution; algorithmic accountability and transparency reporting; automated journalism and content
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, Atmospheric and Oceanic Sciences, Geosciences, Computational Science and Engineering, or a related area is required.The position will involve developing models and algorithms for the evolution of inorganic
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to develop algorithms and methodologies for mapping irrigation patterns using satellite imagery. Investigate methods for detecting the timing and frequency of irrigation events from time-series remote sensing
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), National Animal Disease Center, Virus and Prion Research Unit, located in Ames, Iowa. For an introduction to the Flu crew at the National Animal Disease Center, please see: https://youtu.be/kOJy8tFTuiI About
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such an environment and using this information in control algorithms to ensure robust navigation. This project is funded by the Hauts-de-France Region. Mission The recruited person ensures research work. She will be in
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José Sesé Abad Funding body: CAIB Institution: Universitat de les Illes Balears (UIB) / University of the Balearic Islands (UIB) Where to apply Website https://ppi.uib.eu/ Requirements Research
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to source localization based on microphone arrays or distributed sensors. This PhD project will focus on the development of novel methods and algorithms for airborne noise source localization in generic urban
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PLAN The work plan involves the following tasks: - Design and computational implementation of methods, algorithms, and applications for the Portuguese use case. - Specification and development
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information about the School of Biomedical Engineering, please visit https://www.bme.ubc.ca/ . The computational cancer biology and pathology artificial intelligence team (AI in Medicine Lab) at the University
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Operations Manager to lead and monitor operations for continuous algorithm improvement and validation. This will involve guiding the development of data management systems and establishing data assessment