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focuses on detecting underwater acoustics using AI methodologies. Additionally, CFD simulations combined with physics-informed machine learning will also be examined. Several research and industrial
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increasing importance due to the widespread use of AI and in particular machine learning (ML). As today’s mainstream AI/ML workloads often resort to large-scale and energy-hungry supercomputers, it is
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interdisciplinary and international research environment and is expected to contribute actively to scientific publications, collaborative research activities, and external funding development. You must submit a
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effectively exploited, possibly using some kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several
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change and habitat destruction”, which is an international collaboration between researchers at the University of South-Eastern Norway (USN), the University of the Valley of Guatemala (UVG) and the
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collaboration with the rest of the team, and the fellow is expected to co-author some of the research outputs with members of the team. The fellow will have space to develop their own scholarly profile and is
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inscriptions already collected by the project and are expected to contribute to it through their own research and fieldwork. The research in both work packages will be conducted in close collaboration with
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mission. Careers advice and guidance throughout the entire doctoral programme. Together we will draw up a career plan that includes the skills and knowledge you will acquire. An inclusive working
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four years are expected to acquire basic pedagogical competency in the course of their fellowship period within the duty component of 25 %. Place of work is Department of Bioscience in the new Life
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simulations combined with physics-informed machine learning will also be examined. Several research and industrial partners are a part of this project. The ideal candidate would combine strong computational