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, LangChain, HuggingFace, axolotl. Knowledge of and ability to select, adapt, and effectively use large AI foundational models. Professional experience developing solutions using NLP, computer vision, or
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information exchange (HIE) Natural language processing in clinical/biomedical domains Mobile health, digital health, human–computer interaction in health Learning health systems, community health informatics
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employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ The department's research on responsible and human-centred artificial
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quality monitoring, and/or nature-based water treatment designs. In addition, the candidate should have some experience in AI, machine learning, and/or managing large data sets related to water resources
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more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be
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conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ The department's research on responsible and human-centred artificial intelligence
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conducting research "in the wild" (e.g., field deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an
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or industry equivalent work at a computing facility, or using/managing HPC resources Experience working with large scale machine learning models Experience with performance optimization, debugging, and
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cases. We are particularly interested in how AI, Data Science, or Machine Learning techniques can be used to quantify and assess software and system security from open source software to cloud services
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome