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to support the design and deployment of advanced nuclear reactors. Work effectively individually and within a team to meet the requirements of projects. Communicate effectively the work performed through
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fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, computer science, or a related field completed within
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DOE national laboratories. Excellent written and oral communication skills. Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across
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targeted at the key DOE Office of Science missions. Major Duties/Responsibilities: Work closely with ORNL researchers in using the resources of the OLCF effectively and efficiently Develop and port scalable
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, energy use, and other factors as needed Disseminate research findings in the form of multiple peer-reviewed journal articles per year Prioritizing multiple research projects at once to meet strategic goals
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a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD degree in materials science, nuclear, or mechanical engineering, or a related
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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delivering solutions to pressing energy storage problems essential to economic develop and security of the United States. As part of our research team, the candidate will be expected to work across a variety
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land loss and vegetation change at high spatial resolution Work closely with remote-sensing scientists, modelers, and empiricists across DOE laboratories and universities to address project objectives
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) to work on the Terrestrial Ecosystem Science Scientific Focus Area (TES SFA). The successful candidate will contribute to the development and evaluation of the Energy Exascale Earth System Model's land