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well as the Horizon Europe project High-Performance Language Technologies (HPLT). The group represents extensive experience and expertise in web-scale data curation, development of large language models (LLMs), and in
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consisting of senior researchers and 4 different PhD candidates will investigate the Southern Norwegian North Sea source-to-seep system through analysis of new and existing data from four different
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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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until June 30, 2026 to complete the final exam. Desired qualifications: Experience with implementation or applications of large machine learning models Experience with generative methods for protein
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, and how their combination can improve safety signal detection. As a PhD fellow, you will be working with large-scale longitudinal data, managing data, writing scripts, performing statistical analyses
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application development. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data
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transfer learning, data-driven calibration, or case-based reasoning, to improve decision-making, reduce uncertainty, and justify steering recommendations? This PhD research together with the DigiWells team
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exam before 15.06.2026. It is a condition of employment that the master's degree has been awarded. Background in optimization is required. Experience in machine learning is an advantage. Familiarity with
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, or other neurodegenerative disorders. Experience with machine learning for large datasets. Experience with computational methods and workflows for handling large-scale data. Personal skills Highly organized
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predictions of various observables as function of cosmological parameters. The candidate will develop and use skills in topics such as statistics, high performance programming, machine learning and using data