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safety at ORNL and DOE sites. This position resides in the Performance Engineering group in the Data and AI Systems Section in Computer Science and Mathematics division within Computing and Computational
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expected to be: September 16, 2024 This position is expected to be for 12 months. Candidates should have at least an MS in Computer Science and Engineering or a related field and at least a summer of related
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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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: 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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the aim of developing innovative strategies to improve human health. HT is composed of five Centres: Health Data Science, Genomics, Computational Biology, Neurogenomics and Structural Biology. The Centres
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discipline (e.g. Medical Informatics, Computer Science, Data Science, Computational Social Science, Epidemiology, Biostatistics, etc.) Strong research track record, programming, and implementation skills
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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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. Preferred qualifications PhD or equivalent in Nuclear Engineering, Physics, Chemistry, Materials Science or related disciplines Demonstrated proficiency with computational modeling, e.g., DFT simulations
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at the intersection of computational modeling, data science, and clinical medicine. The successful candidate will work closely with clinicians, intensivists, and computational scientists to develop
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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