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. Writing and communication skills and the ability to publish. Preferred Qualifications: Experience with Multiphysics software and simulations an asset. Previous experience with the development and
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for microscopy, spectroscopy, interferometry, or quantum-optics experiments. Experience acquiring and analyzing experimental data using Python, MATLAB, LabVIEW, or comparable scientific software. Preferred
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for the collection of in-situ mechanical testing data. Knowledge of scientific software in python (numpy, scipy, pandas) or related data analysis suite. Record of productive and creative research as demonstrated by
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community electrification and decarbonization. Understanding for creating, modifying, and analyzing OpenStudio and EnergyPlus building energy models. Strong software development skills for automation of many
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machine learning and Bayesian calibration methods to enable multi-scale, multi-physics model development. Complete simulation verification, model validation, uncertainty quantification, and documentation
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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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, collaborate with interdisciplinary teams, publish in leading scientific venues, and contribute to emerging QHPC software and system technologies. Major Duties/Responsibilities: Develop and evaluate
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-throughput phenotyping at ORNL's Advanced Plant Phenotyping Laboratory (APPL) with paired geochemical and microbial measurements. Utilize laboratory equipment and software that may include a Picarro gas
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implementation of constitutive models within commercial and/or open-source finite element software is required. Preferred Qualifications: Demonstrated expertise in multi-physics FE simulations is preferred
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, quantify nonlinear interactions, and advance scientific understanding of coastal ecosystem resilience. Curate and develop reproducible AI-ready datasets, computational workflows, and research software