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Field
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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monitoring in manufacturing environment Develop modular, extensible workflows for data processing Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal
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have demonstrated experience applying AI and machine learning tools to manage, clean, and code complex nutrient content and food product datasets. Experience with data visualizations, front of pack
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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. Teamwork: Ability to work collaboratively with others and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications
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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | 2 months ago
Biotechnology ), we develop agentic AI and “virtual cell” models in the context of the Human Cell Atlas and the European Lab for Learning & Intelligent Systems , powered by large-scale single-cell, spatial, and
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at the Large Hadron Collider. The successful candidate will play a leadership role in searches for physics beyond the Standard Model, machine learning applications, and Phase-2 trigger upgrades. UIUC is a top 10
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seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making
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. The postdoctoral associate will be expected to work both collaboratively and independently on research projects, advancing computational methods using machine learning, developing automated pipelines for data
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modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected