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Field
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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modeling of x-ray spectroscopies sensitive to molecular chirality; simulations of x-ray–induced ultrafast electron-transfer, decay, and nuclear dynamics in gas- and liquid-phase systems; and the development
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Research Associate to develop and apply computational technique for advanced manufacturing using high-performance computing resources. ORNL’s CCP conduct world-leading research and development in multi-scale
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for its open research pool. Positions are limited duration appointments potentially renewable for up to a total of three years. Potential areas of research include: program development; statistical analyses
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. The scholar will be actively involved in managing clinical trials and serving as a sub-investigator on industry- and investigator-initiated studies while working closely with faculty investigators to develop
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appropriate agencies and Institutions; identify and select problems to be studied; develop and troubleshoot new experimental techniques and protocols; attend research seminars; contribute to manuscript
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in physics preparations for the EIC, the development of advanced accelerator technologies (Argonne Wakefield Accelerator), as well as in the development of novel superconducting detectors
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conduct detailed complex scientific studies, functioning as a subject expert on one or more phases of the project(s). They will prepare and/or present seminars, talks or lectures for dissemination
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multidisciplinary team tackling critical issues in cancer detection and provide support in the applied nanotechnology lab to assist in the development and execution of research projects related to the production and
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for improvement, and/or analyze their impacts at individual, regional and national level. The candidate will also be tasked to develop new ideas into projects under the supervision of more experienced researchers