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intelligence (AI), and analyses changes in trust and understandings, at a time when AI becomes integrated into everyday media experiences. The goal of the project is to develop new conceptualizations of what AI
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collaborative skills. Applicants must be proficient in both written and oral English. Experience from one or several of the following areas is an advantage: Developing algorithms for CFD solvers (e.g. OpenFOAM
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advantage: Developing algorithms for CFD solvers (e.g. OpenFOAM). Programming in C++ or Fortran and proficiency with MATLAB or Python scripting. Experience with tools for simulating chemical kinetic, e.g
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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. To explore and investigate this topic, the project will combine formal methods, programming language theory and semantic technologies, aiming to develop systematic techniques for handling protected data
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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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Excellence. The Center focuses on algorithmic narrativity, new environments and materialities, and the shifting cultural contexts in which digital narratives are received and processed. We investigate the ways
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at the University of Bergen. The Department hosts the Center for Digital Narrative (CDN) , a Norwegian Centre of Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities
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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 domainspecific knowledge with data