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. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological modelling, with an emphasis
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experiments and electron microscopy analysis in collaboration with Prof D. Healy and Prof. S. Piazolo. The postholder will be en-couraged to develop a leadership role within the project, present internal
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at the department) distributed over the employment period. The 4th year is contingent on the qualifications of the candidate and the teaching needs of the department and will be decided by the head of department upon
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Services of the EBRAINS Research Infrastructure - the European distributed research infrastructure for brain and brain-inspired research (https://ebrains.eu ) and leads the Norwegian national node of EBRAINS
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for a 4th year, consisting of 25 % career-promoting work (e.g. teaching responsibilities at the department) distributed over the employment period. The 4th year is contingent on the qualifications
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for investigating non-antibiotic therapies in dentistry (MISFAITH)," led by PI Prof. Håvard J Haugen . The project is funded by the Norwegian Research Council and has several renowned national and international
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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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/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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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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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