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enterprise data into usable models (Snowflake preferred). Experience working with large-scale administrative systems such as Banner, Workday, Salesforce, or ServiceNow. Effective analytical thinking and
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; Forkel et al., Nat Geo, 2025). The student will benefit from access to empirical and remote-sensing data from complementary projects funded through two UK’s Natural Environment Research Council large
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specifications for generative AI. Experimenting with tuning and adapting large language models for spec-driven development. Validating your ideas through empirical studies, prototypes, and real-world data. Why is
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the opportunity to lead research that addresses the technical challenges of large-scale electrification and grid integration. Information As an Assistant/Associate Professor, you will: Lead research on grid
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 27 days ago
to contribute to innovative projects at the forefront of healthcare delivery improvement, leveraging Large Language Models (LLMs) and clinical data analysis. About the Position Our Postdoctoral Research Program
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material for these courses. Full Time. Application Procedures & Deadline Information Please create your candidate profile at https://jobs.illinois.edu and upload your cover letter and resume by 6:00pm (CST
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https://administracion.ulpgc.es/info.1 Requirements Research FieldComputer science » Computer systemsEducation LevelPhD or equivalent Skills/Qualifications Qualifications: Degree in Computer Engineering
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to, data science, statistics, computer science, engineering, mathematics, etc.), along with prior experience analysing electronic health records data from large mental health electronic health records
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psychophysiology, programming (e.g., in Inquisit), or complex data analysis is preferred, but not required; Experiencing with applying for large grant is a plus, but not required; You work proactively and
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(https://qtp.ufl.edu), a multi-disciplinary institute (Physics, Chemistry, Materials Science, and Computer and Information Sciences) focusing on theory, modeling, and computation of complex, novel