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to conceive of, plan, and implement the scientific research, and to report relevant results in publications and conference presentations. The selected individual will have access to state-of-the-art research
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simulation (classical and ab-initio molecular dynamics, DFT, simulations) Proficiency in programming languages like Python, C++, or Fortran for custom analysis tools. Experience in developing workflows
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analysts, and planners who work with the U.S. Department of Energy and other sponsors to assess programs and develop tools for the public to use in calculating potential environmental and economic impacts
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, computational science, a physical science, or engineering or related field. Comprehensive experience programming in one or more programming languages such as Python, C/C++. Experience with one of the AI
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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. Familiarity with techno-economic analysis. Experience with scientific programming languages (e.g., R, Python, Java) and statistical software (e.g., Stata). Ability to create visualizations to effectively
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, Physics, or Chemistry. Knowledge of experimental fluid dynamics. Knowledge of mechanical engineering concepts and procedures. Computer and programming skills, including data processing and manipulation
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computer vision. Experience with multi-modal data fusion and alignment techniques. Experience with spatial transcriptomics or other -omics data analysis. Proficiency in Python programming and scientific
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(electrochemistry, materials synthesis, or characterization) or computational simulations perspective, is required. Proficiency in Python programming is required. Familiarity with REST APIs is desirable. Master’s
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preferred. Strong data analysis skills and ability in programming languages, such as Python, for performing experiments and analyzing data. Knowledge of innovative phase retrieval algorithms is desirable