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, earth sciences, geospatial science, computer science, or a closely related field, completed within the last 5 years. Preferred Qualifications: Prior knowledge and demonstrated expertise in one or more of
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| Mechanical and Aerospace Engineering Performs basic or applied research in the area of computational fluid dynamics and computational aeroacoustics, including problem setup, simulation and advanced post
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 20 hours ago
. Discipline(s): Business (3 ) Chemistry and Materials Sciences (12 ) Computer, Information, and Data Sciences (9 ) Earth and Geosciences (3 ) Engineering (27 ) Mathematics and Statistics (4 ) Other
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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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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workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in evolutionary biology, plant biology, genomics, bioinformatics, mathematics, statistics, computer
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, enzyme kinetics, drug design, X-ray crystallography, single-particle cryoEM, and computational biology. The selected candidate is expected to have good communication skills and the ability to work
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forward to collaborating with software engineers and researchers across all areas of astrophysics and fields such as computer science and statistics. Applicants should demonstrate excellence in research
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: Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related discipline Strong experience in integrating several of the following
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Qualifications • Ph.D. in Civil/Electrical/Mechanical Engineering, Computer Science, Data Science, or a related field • Demonstrated expertise and publication record in computer vision, machine learning, 3D scene