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working with and manipulating large datasets with scripting languages such as Python, or compiled languages such as C++, and Fortran. Experience implementing workflows with API wrappers and software such as
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at conferences. We are looking for: Ph.D. in Materials Science, Chemistry, Physics, Computer Science, or a related field. Demonstrable strong Python programming (programming portfolio required). Experience with
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-to-end GPU timing; document limitations and extrapolation behavior. Implement, test, document, and maintain open-source Python/JAX research software; collaborate with researchers to connect trained models
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related field. Demonstrated knowledge of Python or another major programming language for data analysis and familiarity with machine learning approaches for data analysis. Knowledge of Machine Learning
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with environmental/scientific datasets (cleaning, processing, analysis, synthesis). Strong programming skills, especially Python (or comparable scientific programming). Experience with LLM-assisted
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Python, R or a similar scientific programming language, with a focus on reproducibility and open-source best practices Demonstrated experience in geospatial data analysis and the management of large
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programming in R, Python, or similar, and proficiency in using GitHub and other data management tools; ● Experience summarizing and visualizing data in accessible and compelling formats for non-technical
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experience with managing, processing, and analyzing large datasets and strong programming skills especially in Python. ● Experience working with transmission power flow and machine learning models. ● Strong
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: agrivoltaics, ecovoltaics, solar PV performance modeling, biophysical/crop modeling, or techno-economic assessment (TEA) Advanced proficiency in Python or a similar scientific programming language, with a focus