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) advanced cooling solutions for energy systems; (3) thermal management for electronics and data centers; and (4) separation processes for building environments. Develop experimental setup, problem-solving
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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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choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security
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/Responsibilities: Design and implement a modular ROS 2 software architecture for onboard sensing, autonomy, mapping, data logging, launch management, and configuration management. Develop and integrate ROS 2 drivers
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or program datasets. Proficiency in statistical programming and data analysis tools: R, Python, Stata, or SAS SQL/database management preferred. Ability to clean, harmonize, and analyze complex datasets from
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environmental, safety, health, and quality (ESH&Q) standards and requirements. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork
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-efficient building systems, thermal-fluid processes, industrial heating applications, data center thermal management, and other emerging energy technologies. Develop and operate experimental facilities
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on the physical metallurgy of non-ferrous alloys for various applications including aerospace, automotive, and thermal management applications. Projects will include application of physical metallurgy principles
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MSTD on the physical metallurgy of aluminum alloys for various applications including automotive, aerospace, and thermal management. Projects will include application of physical metallurgy principles
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
. Create and maintain datasets in databases on in-house data storage resources working closely with ORNL’s workflow and data management scientists. Meaningfully collaborate with experimental groups involved