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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
remote work location, consistent with System Office policy. UNC Chapel Hill employees are generally required to reside within a reasonable commuting distance of their assigned duty station. The Data-Driven
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these plants. The post-doc is expected to build upon existing in-house tools and, where applicable, enhance them by means of AI (machine learning) and data-driven methods. These models are aimed to support
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California State University, Northridge | Northridge, California | United States | about 4 hours ago
project-based environment. Experience with advanced analytics, including predictive modeling, data science, or statistical analysis to support data-driven decision-making. Pay, Benefits, & Work Schedule The
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key master data domains (e.g. Person, Organisation, Vendor). The role focuses on identity resolution, survivorship modelling, API-first publishing, and event-driven data architecture — ensuring high
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of Technology , we conduct advanced research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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attitude, ability to work independently as well as in a team. Familiarity with green building technology, HVAC system study and optimization, sustainable building design, building energy modelling, CFD
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AI and related areas such as large language models (LLMs), prompt engineering, and machine learning. You are proactive about staying current in a rapidly evolving field. Rather than waiting for trends
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 9 hours ago
traditional predictive attempts and limits the availability of training data for high-resolution atmospheric and hydrological models. This limitation is compounded by the fact that many atmospheric reanalysis
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models that support operational analytics, strategic reporting, automation, and emerging AI-driven insights. This role is critical to enabling data-informed decisions across academic, administrative, and