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, and validating methods for synthetic data generation that enable secure and trustworthy data sharing and exchange for learning applications. The fellow will design approaches that ensure high data
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of maritime business models. As digital solutions replace manual coordination and increase data-driven transparency, the patterns of supplier relationships, contractual arrangements, and responsibility
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, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning, the project will make use of historical radar
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. More information about project partners is available on the project website here: https://www.ntnu.edu/isa/welgai n Duties of the position The successful applicant will conduct quantitative research with
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must contact HK-dir (Norwegian Directorate for Higher Education and Skills) yourself for recognition of your education: https://hkdir.no/utdanning-fra-utlandet . Specific qualification requirements
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Norwegian master’s degree. Please see https://hkdir.no/en/ for more information about HK-dir’s general recognition. The review process by HK-dir may take some time. Therefore, please submit your application
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PhD candidate in AI-driven ship design, connected to the newly established Norwegian Maritime AI Centre . The position aims to advance how artificial intelligence support ship design processes
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digital solutions replace manual coordination and increase data-driven transparency, the patterns of supplier relationships, contractual arrangements, and responsibility boundaries are likely to change
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to improve detection capabilities, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning
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geopolitical situation. To demonstrate and prototype maritime AI solutions, the center will address a diverse and impactful set of use cases: Logistics, shipping and business transactions; Ship design and