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Is the Job related to staff position within a Research Infrastructure? No Offer Description We seek a PhD-holding research enthusiast, with an interest in developing high-impact research modeling
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a highly motivated candidate for a full-time (100%) PhD position for 3 years in “Development of Probabilistic Reliability Criteria in Distribution Grids”. You will join the research group Power System
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universities, internationally recognized for high quality in research and education. As a societal institution, we shall contribute to sustainable and democratic development and be an attractive and inclusive
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of Biosciences at Blindern, Oslo. Job description The PhD will be hired on the project "HotSpot: Stress-induced mutations in evolution" funded by the NFR and led by William Reinar. The HotSpot project investigates
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sectors. Through research on new methodologies for effective engineering and learning in complex systems, we aim to accelerate innovation and value creation in industry by developing better methods and
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research profile: https://www.hvl.no/en/studies-at-hvl/study-programmes/responsibleinnovation-and-regional-development/ Qualification Requirements Qualification Requirements Applicants must have a relevant
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to the development of next-generation AI-enhanced finite element methods for robust structural design. You will be part of a dynamic and internationally oriented research group with strong expertise in solid mechanics
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methodological challenges in integrative unsupervised learning. Method development will be motivated by the research questions of the funded project, but the candidate will be also free and encouraged to pursue
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collaboration with GE Healthcare and their re-search center in Oslo. Your interests are in neural networks research. You have a big motivation to both contribute to new methods in neural networks, and develop
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collaboration with GE Healthcare and their re-search center in Oslo. Your interests are in neural networks research. You have a big motivation to both contribute to new methods in neural networks, and develop