80 educational-technology-"https:"-"https:"-"https:" Postdoctoral positions at Oak Ridge National Laboratory
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. This position resides in the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL). CSED focuses on transdisciplinary computational science and analytics at scale
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Requisition Id 17038 Overview: We are seeking a Postdoctoral Research Associate with a strong background in organic synthesis and coordination chemistry to develop novel chelation platforms for s
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, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts. This position will remain open for a minimum of 5 days after which it will close when a
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Requisition Id 16569 Overview: The Grid Transients & Advanced Modeling Group in the Electrification and Energy Infrastructure Division (EEID) within the Energy Science and Technology Directorate
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challenges facing the nation. The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral
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professional, academic, and research organizations. Basic Qualifications: A PhD in computer science/engineering or relevant area with an education and a research track record in HPC/AI/edge systems and storage
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physics who are motivated to work across disciplinary boundaries and develop new experimental capabilities. Major Duties/Responsibilities: Design and conduct experiments combining nanoscale photonics
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Materials Science Section, Materials Science and Technology Division, Physical Sciences Directorate at Oak Ridge National Laboratory (ORNL). As part of our research team, you will closely collaborate with a
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, sorption systems, compressors, heat exchangers, HVAC systems, and related technologies. Develop and apply system-level models to support research and design activities. Prepare technical reports, journal
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AI processes (e.g., model training, inference). Develop agentic AI systems and AI harnessing techniques to enhance model quality, resource optimization, and adaptive execution in diverse workflows