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to December 31st 2027) The department Knowledge Technologies for Social Sciences (KTS ) conducts research at the intersection of information retrieval, natural language processing, semantic technologies and
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performance of semantic search and retrieval systems Experience working with a variety of relational SQL and NoSQL databases, big data tools (such as Hadoop, Spark, Kafka), and at least one cloud provider
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thrives in a collaborative, mission-driven environment. The Utah DCC supports large-scale health data infrastructure that underpins national emergency response, clinical registries, and federal research
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thrives in a collaborative, mission-driven environment. The Utah DCC supports large-scale health data infrastructure that underpins national emergency response, clinical registries, and federal research
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stack—including ETL, data models, semantic layers and Power BI—and is now leading the transition to Microsoft Fabric as the modern data platform. Working closely with analysts, service teams and senior
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deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an interest in their application to embodied systems. What
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management, parking and transit, housing, and other institutional platforms. • Build and maintain data solutions within Microsoft Fabric, including lakehouse, warehouse, and semantic model components as
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to obtain information on project limitations and capabilities, performance requirements and interfaces. • Ability to work on small to large projects from analysis through development, testing, QA, and
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to obtain information on project limitations and capabilities, performance requirements and interfaces. • Ability to work on small to large projects from analysis through development, testing, QA, and
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, and curated semantic datasets for analytics and downstream consumption. Develop scalable transformation and modeling layers using dbt (or equivalent) and data modeling best practices (Kimball