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or the adaptation of existing tools and techniques for spatio-temporal analytics, such as representation, exploratory visualization and theories and mathematical model development of spatio-temporal data. Support
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physics is a requirement. A general knowledge of programming languages aimed at scientific data analysis and visualization is a requirement. Hands-on experience with radio, optical, or hard-radiation
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visualization is a requirement. Documented general knowledge of the near-earth space environment, atmospheric or lightning physics is an advantage. Documented general knowledge of space systems design and
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analysis) is a requirement. A general knowledge of programming languages aimed at scientific data analysis and visualization is a requirement. Documented general knowledge of the near-earth space environment
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requirement. A general knowledge of programming languages aimed at scientific data analysis and visualization is a requirement. Documented activity aimed at the calibration of gamma-ray detectors is an
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curating within the fields of contemporary, visual art. The education in the Trondheim Academy of Fine Art seeks to provide theoretical and practical skills in Fine Art including artistic research and
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: Experience with R (data wrangling, visualization, statistical modelling) Experience with experimental methods (e.g., eye-tracking, EEG/ERP, self-paced reading, speech production) Experience working with
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- OsloMet As a PhD Fellow at OsloMet, you have the opportunity to apply for funding for extended research stays abroad . Qualification requirements Master's degree within performing arts, visual arts
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of Informatics. You will be part of Visual Intelligence and the DSB group. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293458/phd-research-fellow-in-deep-learning
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of Computer Science We are the leading academic IT environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual