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large forest resource data using R, Python, and/or GIS software Knowledge of hardwood systems, including management practices, current markets, stand dynamics, environmental change pressures, and
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skills in developing workflows in languages such as R, Google Earth Engine or Python, are desirable Evidence of scientific and technical writing for peer-reviewed publications Demonstrated understanding
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techniques to present findings to stakeholders through technical reports, presentations, and dashboards. Leverage data analysis tools to include SAS, R, python, and visualization tools to advance analytic and
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regular permanent faculty member at an accredited college/university with a research interest in NETL core R&D areas. The ideal candidate would have: Deep understanding for design and optimization
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management, conservation or governance Proficiency with program(s) for qualitative (e.g., NVivo) and quantitative (e.g., R) data analysis Demonstrated ability to problem-solve and conduct research activities
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challenges and R&D needs associated with ammonia combustion - in particular relating to model validation and combustion strategy optimization. Learn about the underlying physics associated with non-thermal
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systems and the agency-wide SCINet computing infrastructure. The participant will also have the opportunity to take online courses in topics such as R, Python, and statistics, and to learn collaboration and