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Analyst. This position will be responsible for providing programmatic and technical support and expertise to the ORNL Classification Program. In this position, you will assist the Classification Officer in
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Qualifications: PhD and 2+ years of experience in a computational discipline such as Computer Science, Statistics, Biomedical Engineering, or a related field. Experience with multi-modal learning across modalities
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respectful workplace – in how we treat one another, work together, and measure success. Required Qualifications: PhD in Nuclear engineering, computer science, applied mathematics, or a related field completed
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-flows. Basic Qualifications: PhD in mathematics, computer science, engineering, or related field earned within the last 5 years. Preferred Qualifications: Experience with mesh generation/CFD applications
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opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: Candidates must have a MS degree or PhD in Nuclear engineering, computer
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: https://www.ornl.gov/content/research-integrity Basic Qualifications: To be eligible you must have completed a PhD in chemistry, physics, engineering, or a related field with in the last 5 years
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Basic Qualifications: A PhD in Mechanical Engineering, Computer Science, or a related field Published technical work in journal articles Presentation experience at conferences Preferred Qualifications
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high-quality delivery of sponsor-funded research. Develop new research proposals, white papers, and program development activities, engaging sponsors and collaborators across government, academia, and
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Qualifications: PhD in chemistry, physics, computer science, materials science, or a related field with no more than five years of postdoctoral experience Preferred Qualifications: Experience in energy‑storage
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. The division leads and supports a vibrant world-class user program while continuing to develop new neutron scattering methods, approaches, and instrumentation, and performing cutting-edge scientific research