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- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- University of Stavanger
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
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, for instance, those based on processes of storytelling, creative writing, cognitive science, narrative theory, and/or theories of creativity. The successful candidate will conduct collaborative as
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writing, cognitive science, narrative theory, and/or theories of creativity. The successful candidate will conduct collaborative as well as their individual research within the Center for Digital
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, or experiences and understandings amongst different groups of citizens. A variety of analytical perspectives and qualitative methods are relevant, including public connection research, folk theory analysis
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groups of citizens. A variety of analytical perspectives and qualitative methods are relevant, including public connection research, folk theory analysis, critical algorithm studies, ethnography and
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, collaborating across disciplines to tackle fundamental challenges through innovative methods, theory and critical analysis. The fellowship period is 3 years. Starting date as soon as possible and upon individual
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research project within the framework of this announcement, leading up to a completed dissertation Learn relevant methods and theories to be used in the research Complete the obligatory training component of
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. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. We do this by combining
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the Research Council of Norway. In this project, we will use advanced time-lapse imaging, numerical simulations, and reactive mixing theories to better understand and predict the role of fluid mixing as a driver
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offers membership of the Norwegian Public Service Pension Fund More about working at UiA. The position is remunerated according to the State Salary Scale, salary plan 17.515, code 1017 PhD Research Fellow