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and analyzing large secondary datasets, including but not limited to administrative claims data, electronic health records, national surveys, and disease registries. The applicant should have advanced
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language processing), machine learning, or data science. Preferred Qualifications Expertise in Deep Learning and LLMs(Large Language Models): Knowledge in building applications and fine-tuning models like Llama 3
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 25 minutes ago
scholar to conduct in-depth analysis of stratospheric data, using data from the Microwave Limb Sounder (MLS) as well as complementary datasets like the Atmospheric Chemistry Experiment Fourier Transform
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, such as learning analytics (from e.g. click-stream data, eye tracking, screen capture etc.), surveys, or other large-scale data analysis. However, we also welcome qualitative or mixed-method approaches
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9 Apr 2026 Job Information Organisation/Company Université de Sherbrooke Department Interdisciplinary Institute for Technological Innovation (3IT) Research Field Engineering » Materials engineering
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population-level outcomes. Utilize advanced quantitative methods to analyze large healthcare datasets, including Medicare and Medicaid claims (MedPAR, Outpatient, Carrier, TAF). Develop reproducible code and
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/Statistics Internal Number: JR101137_1774276539 The Data Science and Statistics Program at the University of Richmond invites applications for a two-year postdoctoral research position in the Distant Viewing
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We are seeking motivated researchers with expertise in large-area 2D materials growth for sensor and transistor applications. The focus is on developing wafer-scale 2D materials using CVD, PLD
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of this position will be based in Oxford, with Dr Will Coulton, and the second 18 months at IPMU, with Dr Leander Thiele. Oxford hosts a large cosmology group with expertise in theoretical, observational, and