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evaluation of the application. The ideal candidate also has experience with teaching at the bachelor- and master level or in a program of professional study or on the PhD level, as well as experience with
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this position is obligated to teach in areas relating to the study programmes for which the faculty/department is responsible at any given time. The person who fills this position is expected to demonstrate a
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on assessing the future evolution and spatial distribution of climatic conditions throughout the entire lifespan of a wind farm. The main objective will be to identify regions with the most favourable climatic
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structural bioinformatics and molecular modeling tools, as well as building on and further developing the datasets and codes from the PePrMInt project (Cf https://doi.org/10.1371/journal.pcbi.1010346
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well as building on and further developing the datasets and codes from the PePrMInt project (Cf https://doi.org/10.1371/journal.pcbi.1010346 ). Qualifications and personal qualities: Applicants must hold a master's
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interdisciplinary collaboration between the Department of Mathematics and the Department of Physics and Technology. The project includes three main activities: (i) the development of novel simulation techniques, (ii
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tasks: Project Design and Planning: Develop and refine the PhD project scope, including objectives, methodology, and detailed plans for data collection and analysis Data Collection and Quality Control
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well as their individual research within the Center for Digital Narrative’s Computational Narrative Systems node, led by Professor Nick Montfort with Professor Rafael Pérez y Pérez. Work includes developing new
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the doctrinal framework and evolution of the intersection between intellectual property law and artificial intelligence. About the LEAD AI fellowship programme LEAD AI is the University of Bergen's career and
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Narrative’s Computational Narrative Systems node, led by Professor Nick Montfort with Professor Rafael Pérez y Pérez. Work includes developing new computational models of narrative and re-implementing