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Field
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to the DOE-funded project, including experimental design, data collection, analysis, and documentation. 20% – Communicate research findings to the broader community through writing and submitting papers
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models. Developing mathematical analysis to bound the trade-off between performance, energy efficiency and time especially in the context of large AI models. Contribute to the research and development
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for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine
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, whose primary activity will be academic research in association with a faculty member or team. The appointee will contribute to research projects focused on conducting statistical analysis of Omics data
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in discovery projects. Coordinate research study activities; lead and manage projects. Oversee organization, synthesis and analysis of data and findings. Prepare scientific reports, outcome findings
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will be on the use of novel ellipsometry techniques to characterize pyrocarbon and graphite-based materials. Analysis will be used to support larger irradiation efforts and interpretation of new fuel
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related field; experience with fMRI experimental design and analysis is not required but highly desired; a strong mathematical/programming skill is highly desired; and a track record of research
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) assess future changes in these patterns under different global warming scenarios. Requirements: The successful applicant should hold a MSc or PhD degree in physics, mathematics/statistics, climate science
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design, optimization, and sizing using phenomenological and/or CFD methods. Energy system analysis. Strong analytical and problem-solving skills, with an ability to interpret and analyze simulation and/or
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related technical field, where prior research experiences in the analysis of aerodynamic noise, vortex sound, and/or wave scattering are highly valued. The postdoctoral scholar will benefit from